Auxo AI

https://auxoai.com

Founded :

2022

Type :

Services

Size :

100-1000

Stage :

Raised funding

About

N/A

Company social profiles

Jobs at Auxo AI

Data Engineer-GenAI

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Hyderabad, Mumbai, Gurugram

4 - 9 yrs

₹15L - ₹45L / yr

Data engineering

Python

Apache Spark

Generative AI

Experience: 4+ Years

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

o End-to-end pipeline development (batch and streaming)

o Data modeling (dimensional, Data Vault, OBT)

o ETL/ELT design patterns, performance tuning, and optimization

o SQL (Advanced) and Python (Advanced)

o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

Experience: 4+ Years

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

o End-to-end pipeline development (batch and streaming)

o Data modeling (dimensional, Data Vault, OBT)

o ETL/ELT design patterns, performance tuning, and optimization

o SQL (Advanced) and Python (Advanced)

o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

Senior Applied Scientist - Semantics

at Auxo AI

Posted by Anupam Arya

Bengaluru (Bangalore), Mumbai, Hyderabad, Delhi, Gurugram

5 - 12 yrs

₹20L - ₹40L / yr

Machine Learning (ML)

Semantics

SPARQL

JSON

Ontology engineering

AuxoAI is seeking a Senior Applied Scientist to design and deploy structured knowledge systems that enable reliable, schema-grounded AI and agent reasoning.

This role sits at the intersection of large language models, knowledge graphs, semantic architectures, and hybrid retrieval systems. The ideal candidate will build systems that transform unstructured data into structured knowledge representations, enforce semantic constraints, and enable hybrid symbolic–neural reasoning in production environments.

You will play a key role in designing scalable semantic infrastructures that support advanced AI use cases such as GraphRAG pipelines, structured extraction, and agent reasoning workflows.

You will work on problems where existing architectures may not be sufficient and will experiment with new approaches that combine machine learning, knowledge graphs, semantic constraints, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Design schema-guided information extraction systems using zero-shot and few-shot structured prompting, constrained decoding approaches such as JSON schema enforcement or grammar-based decoding, and function-calling or tool-driven extraction techniques.
Develop recursive or multi-stage extraction pipelines capable of handling nested entities, hierarchical structures, and cross-document relationships.
Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.

Requirements

5+ years of experience building production AI or machine learning systems.
Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
Experience building entity resolution systems beyond simple embedding similarity methods.
Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
Familiarity with RDF, OWL, or property graph data models and semantic data architectures.
Strong Python engineering skills, with emphasis on data validation, schema integrity, and system reliability.
Experience designing hybrid symbolic and neural AI systems.

Nice to Have:

Experience implementing graph algorithms such as PageRank, community detection, or shortest-path algorithms for reasoning chains.
Experience building graph-enhanced retrieval systems such as GraphRAG.
Experience designing compositional semantic extraction pipelines.
Experience implementing reasoning engines or rule-based inference systems.
Experience benchmarking and evaluating structural extraction accuracy and consistency.

AuxoAI is seeking a Senior Applied Scientist to design and deploy structured knowledge systems that enable reliable, schema-grounded AI and agent reasoning.

You will play a key role in designing scalable semantic infrastructures that support advanced AI use cases such as GraphRAG pipelines, structured extraction, and agent reasoning workflows.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Design schema-guided information extraction systems using zero-shot and few-shot structured prompting, constrained decoding approaches such as JSON schema enforcement or grammar-based decoding, and function-calling or tool-driven extraction techniques.
Develop recursive or multi-stage extraction pipelines capable of handling nested entities, hierarchical structures, and cross-document relationships.
Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.

Requirements

5+ years of experience building production AI or machine learning systems.
Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
Experience building entity resolution systems beyond simple embedding similarity methods.
Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
Familiarity with RDF, OWL, or property graph data models and semantic data architectures.
Strong Python engineering skills, with emphasis on data validation, schema integrity, and system reliability.
Experience designing hybrid symbolic and neural AI systems.

Nice to Have:

Experience implementing graph algorithms such as PageRank, community detection, or shortest-path algorithms for reasoning chains.
Experience building graph-enhanced retrieval systems such as GraphRAG.
Experience designing compositional semantic extraction pipelines.
Experience implementing reasoning engines or rule-based inference systems.
Experience benchmarking and evaluating structural extraction accuracy and consistency.

Senior Applied Scientist - AI Agent Systems

at Auxo AI

Posted by Anupam Arya

Bengaluru (Bangalore), Mumbai, Hyderabad, Delhi, Gurugram

3 - 10 yrs

₹20L - ₹40L / yr

Machine Learning (ML)

Retrieval Augmented Generation (RAG)

Agentic AI

AuxoAI is hiring a Senior Applied Scientist to design and deploy production-grade AI agents capable of structured reasoning, planning, and decision-making.

This role focuses on building reasoning and decision systems using planning algorithms, search methods, and optimization techniques, rather than chatbot or RAG-style application development. The ideal candidate will design intelligent agent architectures that combine LLM-based reasoning with classical planning, search algorithms, and optimization techniques, operating reliably in real-world environments with constraints around latency, cost, uncertainty, and limited context windows.

You will work on advanced AI systems that power autonomous workflows, decision engines, and tool-driven agent ecosystems.

You will also work on problems where existing architectures may not be sufficient, and will be expected to experiment with new approaches that combine machine learning, graph algorithms, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.
Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search, and graph-based planning approaches* to support complex decision-making tasks.
Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.
Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies.
Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.
Develop evaluation frameworks to measure agent performance using task success metrics, rollout simulations, and multi-sample validation approaches.
Improve agent performance through techniques such as distillation, synthetic trajectory generation, prompt compression, and context pruning.
Deliver production-ready agent systems that meet operational requirements around reliability, cost efficiency, throughput, and observability.

Requirements

3-10 years of experience building machine learning or AI systems in production environments.
Strong experience implementing search or planning algorithms beyond basic use cases, including tree search or heuristic-based planning approaches.
Hands-on experience with Monte Carlo Tree Search (MCTS) or related decision-making frameworks.
Strong understanding of state-space representations, heuristic design, and decision boundary trade-offs.
Experience building or extensively customizing agent frameworks for real-world applications.
Hands-on experience designing tool-use or function-calling architectures under practical system constraints.
Strong Python engineering skills with a focus on scalable and reliable system design.

Candidates whose primary experience is limited to RAG pipelines, prompt engineering, or chatbot frameworks without deeper algorithmic or systems work may not be a fit for this role.

Nice to Have:

Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling.
Experience building multi-agent or collaborative agent systems.
Experience designing evaluation frameworks for agent robustness and reliability.
Experience optimizing LLM inference pipelines for latency, throughput, and cost efficiency.
Familiarity with distributed task orchestration systems and large-scale AI workflow management.

AuxoAI is hiring a Senior Applied Scientist to design and deploy production-grade AI agents capable of structured reasoning, planning, and decision-making.

You will work on advanced AI systems that power autonomous workflows, decision engines, and tool-driven agent ecosystems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.
Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search, and graph-based planning approaches* to support complex decision-making tasks.
Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.
Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies.
Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.
Develop evaluation frameworks to measure agent performance using task success metrics, rollout simulations, and multi-sample validation approaches.
Improve agent performance through techniques such as distillation, synthetic trajectory generation, prompt compression, and context pruning.
Deliver production-ready agent systems that meet operational requirements around reliability, cost efficiency, throughput, and observability.

Requirements

3-10 years of experience building machine learning or AI systems in production environments.
Strong experience implementing search or planning algorithms beyond basic use cases, including tree search or heuristic-based planning approaches.
Hands-on experience with Monte Carlo Tree Search (MCTS) or related decision-making frameworks.
Strong understanding of state-space representations, heuristic design, and decision boundary trade-offs.
Experience building or extensively customizing agent frameworks for real-world applications.
Hands-on experience designing tool-use or function-calling architectures under practical system constraints.
Strong Python engineering skills with a focus on scalable and reliable system design.

Candidates whose primary experience is limited to RAG pipelines, prompt engineering, or chatbot frameworks without deeper algorithmic or systems work may not be a fit for this role.

Nice to Have:

Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling.
Experience building multi-agent or collaborative agent systems.
Experience designing evaluation frameworks for agent robustness and reliability.
Experience optimizing LLM inference pipelines for latency, throughput, and cost efficiency.
Familiarity with distributed task orchestration systems and large-scale AI workflow management.

Senior Applied AI Engineer (Computer Vision)

at Auxo AI

Posted by Anupam Arya

Bengaluru (Bangalore), Mumbai, Hyderabad, Delhi, Gurugram

5 - 12 yrs

₹20L - ₹40L / yr

Computer Vision

OpenCV

AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.

This role focuses on building end-to-end visual intelligence systems, combining deep learning, classical computer vision techniques, and multimodal models. It is not limited to model training and requires strong ownership of system design, deployment, and real-world performance.

You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.

You will also work on problems where existing approaches may not be sufficient, and will be expected to combine deep learning, geometric methods, and multimodal reasoning to build robust, production-grade systems.

Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)

Responsibilities:

Design and deploy computer vision systems for tasks such as:
Object detection, segmentation, and tracking
Scene understanding and structured perception
Video understanding and temporal reasoning
Build and optimize models using architectures such as:
CNNs (ResNet, EfficientNet)
Vision Transformers (ViT, Swin, DeiT)
Detection/segmentation models (YOLO, DETR, Mask R-CNN)
Develop multimodal systems combining vision and language:
CLIP-style models
Vision-language models (VLMs)
Visual grounding and captioning systems
Implement algorithms for:
Multi-object tracking (SORT, DeepSORT, ByteTrack)
Feature matching and representation learning
Temporal modeling (RNNs, Transformers for video)
Apply geometric and classical computer vision methods where relevant:
Camera calibration
Epipolar geometry
Pose estimation
3D reconstruction or depth estimation
Optimize systems for:
Low-latency, real-time inference
Throughput and scalability
Edge and distributed deployment
Design and build data pipelines for:
Annotation workflows
Dataset curation
Synthetic data generation
Integrate vision systems into:
Multimodal AI pipelines
Agent-based systems
Decision-making workflows

Requirements:

5+ years of experience building computer vision systems in production environments
Strong experience with deep learning frameworks (PyTorch / TensorFlow)
Hands-on experience with:
Detection, segmentation, or tracking systems
Model training, fine-tuning, and evaluation
Strong understanding of:
Representation learning
Loss functions (contrastive loss, focal loss, etc.)
Evaluation metrics (mAP, IoU, precision/recall)
Experience building and deploying end-to-end vision systems, not just training models

Candidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.

Nice to Have:

Experience with multimodal systems (vision + language)
Familiarity with models such as:
CLIP, BLIP, Flamingo, or similar
Experience with 3D vision:
NeRFs
SLAM
Point clouds
Experience with video understanding:
Action recognition
Event detection
Experience building data engines:
Active learning
Hard negative mining
Experience working with large-scale datasets and distributed training pipelines

AuxoAI is hiring a Senior Applied AI Engineer to design and deploy production-grade computer vision systems that operate reliably in real-world environments.

You will work on systems that perform perception, understanding, and reasoning over visual data, and integrate these capabilities into larger AI platforms and agent-based workflows.

Location – Mumbai / Bangalore / Hyderabad / Gurgaon (Hybrid – 3 days per week in office)

Responsibilities:

Design and deploy computer vision systems for tasks such as:
Object detection, segmentation, and tracking
Scene understanding and structured perception
Video understanding and temporal reasoning
Build and optimize models using architectures such as:
CNNs (ResNet, EfficientNet)
Vision Transformers (ViT, Swin, DeiT)
Detection/segmentation models (YOLO, DETR, Mask R-CNN)
Develop multimodal systems combining vision and language:
CLIP-style models
Vision-language models (VLMs)
Visual grounding and captioning systems
Implement algorithms for:
Multi-object tracking (SORT, DeepSORT, ByteTrack)
Feature matching and representation learning
Temporal modeling (RNNs, Transformers for video)
Apply geometric and classical computer vision methods where relevant:
Camera calibration
Epipolar geometry
Pose estimation
3D reconstruction or depth estimation
Optimize systems for:
Low-latency, real-time inference
Throughput and scalability
Edge and distributed deployment
Design and build data pipelines for:
Annotation workflows
Dataset curation
Synthetic data generation
Integrate vision systems into:
Multimodal AI pipelines
Agent-based systems
Decision-making workflows

Requirements:

5+ years of experience building computer vision systems in production environments
Strong experience with deep learning frameworks (PyTorch / TensorFlow)
Hands-on experience with:
Detection, segmentation, or tracking systems
Model training, fine-tuning, and evaluation
Strong understanding of:
Representation learning
Loss functions (contrastive loss, focal loss, etc.)
Evaluation metrics (mAP, IoU, precision/recall)
Experience building and deploying end-to-end vision systems, not just training models

Candidates whose primary experience is limited to academic projects or model experimentation without real-world deployment may not be a fit for this role.

Nice to Have:

Experience with multimodal systems (vision + language)
Familiarity with models such as:
CLIP, BLIP, Flamingo, or similar
Experience with 3D vision:
NeRFs
SLAM
Point clouds
Experience with video understanding:
Action recognition
Event detection
Experience building data engines:
Active learning
Hard negative mining
Experience working with large-scale datasets and distributed training pipelines

Senior Data Scientist - AI & ML

at Auxo AI

Posted by Anupam Arya

Bengaluru (Bangalore), Mumbai, Delhi, Gurugram, Hyderabad

5 - 12 yrs

₹30L - ₹40L / yr

Machine Learning (ML)

Deep Learning

Generative AI (GenAI)

AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems — including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Own the full ML lifecycle: model design, training, evaluation, deployment
Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
Build agentic workflows for reasoning, planning, and decision-making
Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
Collaborate with product and engineering teams to integrate AI models into business applications
Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices

Requirements

5+ years of experience in designing, deploying, and scaling ML/DL systems in production
Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
Strong software engineering background with experience in testing, version control, and APIs
Proven ability to balance innovation with scalable deployment
B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
Bonus: Open-source contributions, GenAI research, or applied systems at scale

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

Own the full ML lifecycle: model design, training, evaluation, deployment
Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
Build agentic workflows for reasoning, planning, and decision-making
Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines
Collaborate with product and engineering teams to integrate AI models into business applications
Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices

Requirements

5+ years of experience in designing, deploying, and scaling ML/DL systems in production
Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows
Strong software engineering background with experience in testing, version control, and APIs
Proven ability to balance innovation with scalable deployment
B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
Bonus: Open-source contributions, GenAI research, or applied systems at scale

Senior Data Engineer - AWS

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram

6 - 11 yrs

₹15L - ₹50L / yr

Data engineering

Amazon Web Services (AWS)

ETL

SQL

NOSQL Databases

About AuxoAI:

AuxoAI is a global platform-based services firm. We help companies—turn their strategies into practical digital and AI solutions. By understanding how our clients make decisions, we use digital and Artificial Intelligence (AI) technologies to drive growth, enhance their operations, improve customer experiences, and provide clear, actionable insights from their data. What We Do We work across various industries such as healthcare, high-tech, consumer packaged goods (CPG), finance etc., and in sales, marketing, and customer support functions.

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

We are seeking a skilled and experienced Data Engineer to join our dynamic team. The ideal candidate will have 6+ years of prior experience in data engineering, with a strong background in AWS (Amazon Web Services) technologies. This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

About AuxoAI:

We help our clients with accelerating their digital and AI journeys through:

• AI Application Development

• Data, Digital and Cloud acceleration using AI

• AI Native Product Engineering

Responsibilities:

* Design, develop, and maintain scalable data pipelines and ETL processes leveraging AWS services such as S3, Glue, EMR, Lambda, and Redshift.

* Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

* Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

* Implement data governance and security best practices to ensure compliance and data integrity.

* Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

* Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Requirements :

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

* 6+ years of prior experience in data engineering, with a focus on designing and building data pipelines.

* Proficiency in AWS services, particularly S3, Glue, EMR, Lambda, and Redshift.

* Strong programming skills in languages such as Python, Java, or Scala.

* Experience with SQL and NoSQL databases, data warehousing concepts, and big data technologies.

* Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools (e.g., Apache Airflow) is a plus.

Full Stack Engineer (Frontend Focus)

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram

3 - 10 yrs

₹10L - ₹55L / yr

Fullstack Developer

React.js

Javascript

TypeScript

HTML/CSS

+3 more

Role : Senior Full Stack Engineer (Frontend Focus)

Location : Hyderabad/Bangalore/Gurgaon/Mumbai

Role Summary

We're looking for a **Senior Full Stack Engineer (Frontend Focus)** to build modern, AI-powered enterprise applications. You'll primarily focus on creating scalable, high-performance frontend experiences using React and Next.js, while contributing to backend services, APIs, and AI integrations where needed. You'll work closely with Product, Design, and AI teams to build intuitive, performant, and production-ready applications.

Minimum Qualifications

* 3–7 years of software engineering experience.

* Strong experience with React, Next.js, TypeScript, JavaScript, HTML, and CSS.

* Experience building and shipping production-grade frontend applications, including enterprise dashboards and data-intensive applications.

* Strong understanding of frontend architecture, state management (Redux, Zustand, Context API, or similar), rendering lifecycle, and performance optimization, including code splitting, lazy loading, bundle optimization, caching strategies, and Core Web Vitals.

* Experience building complex UI experiences using modern frontend technologies, including data visualization, Canvas, WebGL, Service Workers, and Web Workers.

* Experience building and integrating REST APIs and backend services using Node.js.

Preferred Qualifications

* Experience building AI-powered applications or AI agents using LangChain, LlamaIndex, CrewAI, or similar AI frameworks.

* Experience with vector databases and Retrieval-Augmented Generation (RAG) applications.

* Experience with DevOps practices and cloud platforms such as AWS, Azure, or GCP.

* Experience with Docker and Kubernetes.

* Experience building reusable component libraries, design systems, or micro-frontend architectures.

Role : Senior Full Stack Engineer (Frontend Focus)

Location : Hyderabad/Bangalore/Gurgaon/Mumbai

Role Summary

Minimum Qualifications

* 3–7 years of software engineering experience.

* Strong experience with React, Next.js, TypeScript, JavaScript, HTML, and CSS.

* Experience building and shipping production-grade frontend applications, including enterprise dashboards and data-intensive applications.

* Experience building complex UI experiences using modern frontend technologies, including data visualization, Canvas, WebGL, Service Workers, and Web Workers.

* Experience building and integrating REST APIs and backend services using Node.js.

Preferred Qualifications

* Experience building AI-powered applications or AI agents using LangChain, LlamaIndex, CrewAI, or similar AI frameworks.

* Experience with vector databases and Retrieval-Augmented Generation (RAG) applications.

* Experience with DevOps practices and cloud platforms such as AWS, Azure, or GCP.

* Experience with Docker and Kubernetes.

* Experience building reusable component libraries, design systems, or micro-frontend architectures.

GCP Delivery Lead

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram

10 - 19 yrs

₹20L - ₹75L / yr

Google Cloud Platform (GCP)

Presales

Role Summary

The GCP Delivery Lead is responsible for driving the technical vision, architecture, and delivery of enterprise-scale solutions on Google Cloud Platform (GCP). This role combines deep technical expertise with strong delivery leadership and customer engagement capabilities, working closely with clients, Google teams, and internal stakeholders.

Key Responsibilities

Technical Leadership

Define and own GCP solution architecture and technical strategy for client engagements
Design scalable, secure, and resilient cloud-native architectures
Establish architecture standards, best practices, and reusable frameworks
Provide governance and oversight across multiple programs

Delivery Leadership

Ensure successful delivery of cloud transformation and modernization initiatives
Conduct architecture reviews, risk assessments, and quality assurance
Guide engineering teams through complex implementations
Ensure solutions meet performance, security, and scalability standards

Google Partnership & Pre-Sales

Act as primary technical interface with Google Cloud teams
Support joint solutioning, co-selling, and client workshops
Contribute to proposals, solution design, and executive presentations

AI & Data Solutions

Lead enterprise AI, GenAI, and data platform architecture on GCP
Drive adoption of Vertex AI, BigQuery, and modern AI/ML platforms
Advise clients on AI strategy, transformation, and innovation

Practice Development

Build and mentor high-performing architecture and engineering teams
Drive certifications, capability building, and hiring initiatives
Create accelerators, reusable assets, and reference architectures
Contribute to practice growth and go-to-market strategies

Required Qualifications

Experience

12+ years in cloud architecture, software engineering, or consulting
5+ years of hands-on GCP architecture and delivery experience
Proven track record in large-scale cloud transformation programs
Experience managing multi-client and multi-program delivery

Role Summary

Key Responsibilities

Technical Leadership

Define and own GCP solution architecture and technical strategy for client engagements
Design scalable, secure, and resilient cloud-native architectures
Establish architecture standards, best practices, and reusable frameworks
Provide governance and oversight across multiple programs

Delivery Leadership

Ensure successful delivery of cloud transformation and modernization initiatives
Conduct architecture reviews, risk assessments, and quality assurance
Guide engineering teams through complex implementations
Ensure solutions meet performance, security, and scalability standards

Google Partnership & Pre-Sales

Act as primary technical interface with Google Cloud teams
Support joint solutioning, co-selling, and client workshops
Contribute to proposals, solution design, and executive presentations

AI & Data Solutions

Lead enterprise AI, GenAI, and data platform architecture on GCP
Drive adoption of Vertex AI, BigQuery, and modern AI/ML platforms
Advise clients on AI strategy, transformation, and innovation

Practice Development

Build and mentor high-performing architecture and engineering teams
Drive certifications, capability building, and hiring initiatives
Create accelerators, reusable assets, and reference architectures
Contribute to practice growth and go-to-market strategies

Required Qualifications

Experience

12+ years in cloud architecture, software engineering, or consulting
5+ years of hands-on GCP architecture and delivery experience
Proven track record in large-scale cloud transformation programs
Experience managing multi-client and multi-program delivery

AWS Delivery Lead

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram

10 - 19 yrs

₹20L - ₹75L / yr

Amazon Web Services (AWS)

Presales

AWS Delivery Lead

Location: Mumbai / Bangalore / Gurgaon / Hyderabad

Role Summary

The AWS Practice Lead is a senior technical leader responsible for driving AWS architecture, delivery excellence, customer engagement, and practice growth at AuxoAI. This role involves designing enterprise-scale cloud and AI solutions, leading cross-functional teams, and working closely with AWS stakeholders to position AuxoAI as a leading Enterprise AI and Cloud Transformation partner.

Key Responsibilities

1. Technical Leadership

Define and drive AWS architecture strategy across engagements
Design scalable, secure, resilient, and cost-effective solutions
Establish architecture standards, governance, and best practices
Lead architecture reviews and provide oversight on complex programs

2. Delivery Leadership

Partner with delivery and account teams to ensure successful execution
Guide engineering teams on technical decisions and challenges
Ensure delivery quality aligned with AWS Well-Architected principles
Identify and mitigate risks across projects

3. AWS Partnership & Customer Engagement

Act as the technical lead for AWS partnership initiatives
Collaborate with AWS teams on joint opportunities
Lead customer workshops, executive briefings, and solution design sessions
Support pre-sales, proposals, and technical presentations

4. AI & Data Innovation

Lead AI/ML, Generative AI, and data analytics solutions on AWS
Architect modern AI applications using AWS services (e.g., Bedrock, SageMaker)
Advise customers on AI adoption, modernization, and data strategy
Drive innovations in GenAI, Agentic AI, and automation

5. Practice Building

Build and mentor AWS architecture and engineering teams
Drive certifications and skill development
Create reusable frameworks, accelerators, and best practices
Support hiring and growth of the AWS practice

Required Qualifications

Experience

12+ years in cloud architecture / consulting / enterprise technology
5+ years of hands-on AWS architecture experience
Proven expertise in large-scale cloud transformation programs
Strong stakeholder management and consulting skills

Technical Skills

AWS Core: EC2, S3, RDS, VPC, IAM, Route 53, ELB, Control Tower
Cloud Native & DevOps: EKS, ECS, Lambda, API Gateway, Terraform, CI/CD
Data & Analytics: Redshift, Glue, Athena, EMR, Kinesis
Security & Governance: Security Hub, GuardDuty, KMS, CloudTrail
AI/ML & GenAI: Bedrock, SageMaker, LLMs, RAG, vector DBs, MLOps

Leadership Skills

Strong communication and executive presentation abilities
Experience leading workshops and influencing stakeholders
Proven team mentoring and leadership capabilities
Customer-centric mindset with strong business acumen

Preferred Qualifications

AWS Certifications (Solutions Architect Professional, DevOps, ML, Security)
Experience with AWS Partner Network (APN) and co-sell programs
Multi-cloud exposure (Azure/GCP)
Experience delivering AI/GenAI solutions for enterprise clients
Exposure to regulated industries (BFSI, Healthcare, Telecom, etc.)

Success Metrics

Successful delivery of strategic AWS engagements
Growth in AWS services revenue and customer satisfaction
Expansion of AWS partnerships and go-to-market initiatives
Increase in AWS-certified talent and reusable solution assets
Establishment of AuxoAI as a trusted AWS & AI transformation partner

AWS Delivery Lead

Location: Mumbai / Bangalore / Gurgaon / Hyderabad

Role Summary

Key Responsibilities

1. Technical Leadership

Define and drive AWS architecture strategy across engagements
Design scalable, secure, resilient, and cost-effective solutions
Establish architecture standards, governance, and best practices
Lead architecture reviews and provide oversight on complex programs

2. Delivery Leadership

Partner with delivery and account teams to ensure successful execution
Guide engineering teams on technical decisions and challenges
Ensure delivery quality aligned with AWS Well-Architected principles
Identify and mitigate risks across projects

3. AWS Partnership & Customer Engagement

Act as the technical lead for AWS partnership initiatives
Collaborate with AWS teams on joint opportunities
Lead customer workshops, executive briefings, and solution design sessions
Support pre-sales, proposals, and technical presentations

4. AI & Data Innovation

Lead AI/ML, Generative AI, and data analytics solutions on AWS
Architect modern AI applications using AWS services (e.g., Bedrock, SageMaker)
Advise customers on AI adoption, modernization, and data strategy
Drive innovations in GenAI, Agentic AI, and automation

5. Practice Building

Build and mentor AWS architecture and engineering teams
Drive certifications and skill development
Create reusable frameworks, accelerators, and best practices
Support hiring and growth of the AWS practice

Required Qualifications

Experience

12+ years in cloud architecture / consulting / enterprise technology
5+ years of hands-on AWS architecture experience
Proven expertise in large-scale cloud transformation programs
Strong stakeholder management and consulting skills

Technical Skills

AWS Core: EC2, S3, RDS, VPC, IAM, Route 53, ELB, Control Tower
Cloud Native & DevOps: EKS, ECS, Lambda, API Gateway, Terraform, CI/CD
Data & Analytics: Redshift, Glue, Athena, EMR, Kinesis
Security & Governance: Security Hub, GuardDuty, KMS, CloudTrail
AI/ML & GenAI: Bedrock, SageMaker, LLMs, RAG, vector DBs, MLOps

Leadership Skills

Strong communication and executive presentation abilities
Experience leading workshops and influencing stakeholders
Proven team mentoring and leadership capabilities
Customer-centric mindset with strong business acumen

Preferred Qualifications

AWS Certifications (Solutions Architect Professional, DevOps, ML, Security)
Experience with AWS Partner Network (APN) and co-sell programs
Multi-cloud exposure (Azure/GCP)
Experience delivering AI/GenAI solutions for enterprise clients
Exposure to regulated industries (BFSI, Healthcare, Telecom, etc.)

Success Metrics

Successful delivery of strategic AWS engagements
Growth in AWS services revenue and customer satisfaction
Expansion of AWS partnerships and go-to-market initiatives
Increase in AWS-certified talent and reusable solution assets
Establishment of AuxoAI as a trusted AWS & AI transformation partner

MDM Data Specialist

at Auxo AI

Posted by Hema Dekonda

Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram

3 - 15 yrs

₹15L - ₹45L / yr

MDM

Informatica MDM

Data modeling

Data governance

Role: MDM Data Specialist

Location: Bangalore/Hyderabad/Gurgaon/Mumbai

Key Responsibilities

Manage and improve master data across customer, product, entitlement, account hierarchy, product catalog, subscription, contract, billing, and revenue domains.
Configure and support MDM platform capabilities, including data models, match and merge rules, survivorship rules, hierarchy management, validation rules, workflows, reference data, and data quality rules.
Support integration of master data between MDM platforms and operational systems such as Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, billing, ERP, data lake, and reporting platforms.
Assist with customer golden record creation, account hierarchy management, deduplication, data standardization, and Customer 360 enablement.
Support product taxonomy and product catalog data needed for CPQ bundles, pricing rules, eligibility rules, commercial BOMs, and quote-to-cash automation.
Maintain entitlement and subscription data, including customer-to-product mappings, lifecycle status, renewals, amendments, upsells, and install base visibility.
Perform data profiling, cleansing, reconciliation, validation, issue resolution, and root-cause analysis across multiple systems.
Document data definitions, business rules, source-to-target mappings, lineage, stewardship processes, and remediation actions.
Partner with Sales Operations, Revenue Operations, Finance, Product Operations, Customer Success, IT, Data Governance, and Enterprise Architecture teams.

Required Qualifications

3-7+ years of experience in master data management, data governance, data quality, data operations, revenue operations, sales operations, product operations, or a related data role.
Hands-on experience with an MDM platform such as Informatica MDM, Informatica IDMC, Reltio, or a comparable enterprise MDM solution.
Experience in a SaaS, subscription, technology, or enterprise software environment.
Working knowledge of CRM, CPQ, quote-to-cash, order-to-cash, billing, entitlement, subscription, contract, or revenue management processes.
Experience with customer master, product master, product catalog, account hierarchy, entitlement, subscription, contract, billing, or revenue data.
Understanding of MDM concepts such as golden record, match/merge, survivorship, reference data, hierarchy management, stewardship workflows, data quality rules, and cross-system synchronization.
Strong analytical skills with the ability to investigate data issues across business processes and systems.
Experience with data profiling, cleansing, standardization, deduplication, validation, reconciliation, and remediation.
Strong documentation, communication, and stakeholder management skills.

Preferred Qualifications

Experience with Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, or broader Salesforce ecosystem data models.
Experience integrating MDM platforms with Salesforce, CPQ, billing, ERP, data warehouse, or lakehouse environments.
Experience with Informatica Customer 360, Product 360, Reference 360, Cloud Data Quality, Cloud Data Governance, or Reltio Connected Data Platform / Reltio Data Cloud.
Familiarity with APIs, batch integrations, event-driven integrations, data pipelines, data lineage, metadata management, and access controls.
Experience with CPQ product structures, bundles, pricing rules, discounting, quote lines, contracts, assets, subscriptions, and renewals.
Familiarity with revenue management concepts such as ASC 606, IFRS 15, performance obligations, revenue recognition, and SOX controls.
Experience with SQL, Excel, BI tools, data profiling tools, data catalogs, or cloud data platforms.
Experience supporting quote-to-cash transformation, M&A data onboarding, or enterprise data modernization.

Role: MDM Data Specialist

Location: Bangalore/Hyderabad/Gurgaon/Mumbai

Key Responsibilities

Manage and improve master data across customer, product, entitlement, account hierarchy, product catalog, subscription, contract, billing, and revenue domains.
Configure and support MDM platform capabilities, including data models, match and merge rules, survivorship rules, hierarchy management, validation rules, workflows, reference data, and data quality rules.
Support integration of master data between MDM platforms and operational systems such as Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, billing, ERP, data lake, and reporting platforms.
Assist with customer golden record creation, account hierarchy management, deduplication, data standardization, and Customer 360 enablement.
Support product taxonomy and product catalog data needed for CPQ bundles, pricing rules, eligibility rules, commercial BOMs, and quote-to-cash automation.
Maintain entitlement and subscription data, including customer-to-product mappings, lifecycle status, renewals, amendments, upsells, and install base visibility.
Perform data profiling, cleansing, reconciliation, validation, issue resolution, and root-cause analysis across multiple systems.
Document data definitions, business rules, source-to-target mappings, lineage, stewardship processes, and remediation actions.
Partner with Sales Operations, Revenue Operations, Finance, Product Operations, Customer Success, IT, Data Governance, and Enterprise Architecture teams.

Required Qualifications

3-7+ years of experience in master data management, data governance, data quality, data operations, revenue operations, sales operations, product operations, or a related data role.
Hands-on experience with an MDM platform such as Informatica MDM, Informatica IDMC, Reltio, or a comparable enterprise MDM solution.
Experience in a SaaS, subscription, technology, or enterprise software environment.
Working knowledge of CRM, CPQ, quote-to-cash, order-to-cash, billing, entitlement, subscription, contract, or revenue management processes.
Experience with customer master, product master, product catalog, account hierarchy, entitlement, subscription, contract, billing, or revenue data.
Understanding of MDM concepts such as golden record, match/merge, survivorship, reference data, hierarchy management, stewardship workflows, data quality rules, and cross-system synchronization.
Strong analytical skills with the ability to investigate data issues across business processes and systems.
Experience with data profiling, cleansing, standardization, deduplication, validation, reconciliation, and remediation.
Strong documentation, communication, and stakeholder management skills.

Preferred Qualifications

Experience with Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, or broader Salesforce ecosystem data models.
Experience integrating MDM platforms with Salesforce, CPQ, billing, ERP, data warehouse, or lakehouse environments.
Experience with Informatica Customer 360, Product 360, Reference 360, Cloud Data Quality, Cloud Data Governance, or Reltio Connected Data Platform / Reltio Data Cloud.
Familiarity with APIs, batch integrations, event-driven integrations, data pipelines, data lineage, metadata management, and access controls.
Experience with CPQ product structures, bundles, pricing rules, discounting, quote lines, contracts, assets, subscriptions, and renewals.
Familiarity with revenue management concepts such as ASC 606, IFRS 15, performance obligations, revenue recognition, and SOX controls.
Experience with SQL, Excel, BI tools, data profiling tools, data catalogs, or cloud data platforms.
Experience supporting quote-to-cash transformation, M&A data onboarding, or enterprise data modernization.

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