Auxo AI

Role: Full Stack Engineer

Location: Hyderabad/Mumbai/Bangalore/Gurgaon

Required Experience: 4-7 years

Role Summary:

We are looking for Software Engineers with deep experience in building highly scalable and reliable enterprise applications. We are looking for engineers who have experience building cloud based/cloud native solutions from scratch. This includes demonstrable expertise in an enterprise friendly backend framework. We expect the engineer to work in a team consisting of Project Managers, Designers, Data Scientists and Software Architects. This is an exciting opportunity to work in a fast paced and innovative environment along with a group of world class and entrepreneurial professionals.

Responsibilities:

• Design and develop user-friendly web interfaces using HTML, CSS, and JavaScript.

• Utilize modern frontend frameworks and libraries such as React, Angular, or Vue.js to build dynamic and responsive web applications.

• Develop and maintain server-side logic using programming languages such as Java, Python, Ruby, Node.js, or PHP.

• Build and manage APIs for seamless communication between the frontend and backend systems.

• Integrate third-party services and APIs to enhance application functionality.

• Implement CI/CD pipelines to automate testing, integration, and deployment processes.

• Monitor and optimize the performance of web applications to ensure a high-quality user experience.

• Stay up-to-date with emerging technologies and industry trends to continuously improve development processes and application performance.

Qualifications:

• Bachelors/Masters in Computer Science or related subjects or hands-on experience demonstrating working understanding of software applications.

• Knowledge of building applications that can be deployed in a cloud environment or are cloud native applications.

• Strong expertise in building backend applications using Java/C#/Python with demonstrable experience in using frameworks such as Spring/Vertx/.Net/FastAPI.

 • Deep understanding of enterprise design patterns, API development and integration and Test-Driven Development (TDD)

• Working knowledge in building applications that leverage databases such as PostgreSQL, MySQL, MongoDB, Neo4J or storage technologies such as AWS S3, Azure Blob Storage.

• Hands-on experience in building enterprise applications adhering to their needs of security and reliability.

• Hands-on experience building applications using one of the major cloud providers, preferably GCP.

• Working knowledge of CI/CD tools for application integration and deployment.

• Working knowledge of using reliability tools to monitor the performance of the application.

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

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 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 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 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 

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.

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 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 

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