Auxo AI

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 

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 Summary:

We are seeking an experienced Master Data Management Specialist to support an enterprise Oracle Fusion Transformation. This role will focus on master data readiness, data quality, governance, migration support, and boundary-system alignment across key business domains.

The ideal candidate has hands-on experience with ERP transformation programs, preferably Oracle Fusion Cloud, and understands master data in a food manufacturing, process manufacturing, CPG, or regulated supply chain environment.

Location: Hyderabad, Bangalore, Gurgaon and Mumbai.

Key Responsibilities

• Support master data readiness for Oracle Fusion design, build, mock loads, UAT, cutover, and hypercare.
• Perform data profiling, cleansing, deduplication, validation, and remediation tracking.
• Create and maintain source-to-target mappings from legacy systems to Oracle Fusion.
• Support data migration cycles, mock load validation, reconciliation, and data defect resolution.
• Partner with IT, business data owners, system integrators, and data stewards to define ownership, rules, and approval workflows.
• Support boundary-system data contracts, including field-level rules, ID crosswalks, downstream integration impacts, and reconciliation controls.
• Help establish sustainable data quality metrics, monitoring, lineage, and stewardship processes.
• Support reporting and analytics readiness by ensuring trusted master data dimensions and consistent reference data.
• Data domains scope:

o   Customer, supplier, contact, and trading partner master data.

o   Product, item, SKU, BOM, specification, category, and UOM data.

o   Location, site, plant, warehouse, address, and inventory location data.

o   Finance master data, including chart of accounts, legal entities, ledgers, cost centers, and hierarchies.

o   Workforce / HCM reference data, including workers, jobs, positions, departments, and organization structures.

o   Reference data such as tax codes, payment terms, value sets, shipping methods, and lookup values.

o   Quality, specification, traceability, asset, equipment, recipe, formula, routing data.

Required Experience

• 10+ years of experience in MDM, data governance, data quality, ERP data migration, or enterprise data management.
• Hands-on experience supporting ERP implementation or transformation programs.
• Strong knowledge of master data lifecycle management, data stewardship, and data quality controls.
• Experience with data profiling, cleansing, deduplication, validation, reconciliation, and defect management.
• Experience developing source-to-target mappings, transformation rules, and data load validation support.
• Ability to work across IT, business teams, system integrators, and data owners.
• Strong documentation, analytical, and issue-resolution skills.
• 
  

Preferred Experience

• Oracle Fusion Cloud ERP experience.
• Oracle Product Hub, Oracle SCM, Oracle Procurement, Oracle Financials, or Oracle MDM experience.
• Food manufacturing, CPG, process manufacturing, or regulated supply chain experience.
• Experience with product/item, supplier, customer, plant/location, quality, recipe/formula, BOM, routing, or traceability data.
• Experience with boundary systems such as PLM, QMS, EAM, CRM, procurement platforms, legacy ERP, data warehouse, or reporting tools.
• Experience supporting mock loads, UAT, cutover, hypercare, and post-go-live data operations.

We are seeking a SAP Functional Consultant with experience in SAP S/4HANA and core manufacturing and supply chain processes, including Materials Management (MM), Production Planning (PP), Quality Management (QM), and Plant Maintenance (PM).

The ideal candidate will possess strong functional knowledge of SAP processes, hands-on configuration experience, and the ability to work closely with business and technology teams to support SAP implementation, enhancement, and transformation initiatives.

Key Responsibilities

• Support SAP functional design, configuration, testing, and deployment activities across MM, PP, QM, and PM modules.

• Gather and analyze business requirements and assist in translating them into SAP solutions.

• Configure and support business processes including:

o Materials Management and Procurement

o Production Planning and Manufacturing Operations

o Quality Management

o Plant Maintenance

o Inventory Management

o Master Data Management

• Participate in SAP S/4HANA implementation, enhancement, migration, and support projects.

• Assist in fit-gap analysis, process mapping, and solution design activities.

• Collaborate with technical teams on integrations, reports, interfaces, conversions, and enhancements.

• Support testing activities including SIT, UAT, defect resolution, and deployment validation.

• Prepare functional specifications, process documentation, training materials, and user guides.

• Support go-live activities, hypercare, and post-production support.

• Work closely with business users to troubleshoot issues and identify process improvement opportunities.

Required Skills & Experience

• 3–6 years of SAP functional consulting experience.

• Hands-on experience in one or more of the following SAP modules:

o SAP Materials Management (MM)

o SAP Production Planning (PP)

o SAP Quality Management (QM)

o SAP Plant Maintenance (PM)

• Experience working with SAP S/4HANA environments.

• Understanding of manufacturing, supply chain, procurement, inventory, and maintenance business processes.

• Experience supporting requirements gathering, configuration, testing, and deployment activities.

• Strong analytical, problem-solving, and communication skills.

• Ability to work effectively in a collaborative, team-oriented environment.

Preferred Qualifications

• Exposure to SAP Integrated Business Planning (IBP).

• Exposure to SAP Ariba and procurement processes.

• Experience supporting SAP ECC to S/4HANA migration initiatives.

• SAP certification in MM, PP, QM, PM, or S/4HANA.

• Experience working in manufacturing, life sciences, medical devices, consumer products, or supply chain-intensive industries.

What You'll Bring

• Strong functional and analytical capabilities.

• Ability to understand business requirements and translate them into SAP solutions.

• A proactive learning mindset and willingness to expand expertise across SAP modules.

• Strong collaboration and stakeholder engagement skills.

• Passion for driving operational excellence through SAP-enabled business processes.

AuxoAI is seeking a skilled and experienced Senior AI Engineers to join our dynamic team. The ideal candidate will have 5+ years of prior experience in software engineering. This role involves collaborating with cross-functional teams to drive innovation and deliver impactful AI-driven products. This role is responsible for implementing our strategic direction on AI, intelligent automation, and data-powered operations. This role will also guide the implementation of AI solutions across various projects, with an eye on AI governance.

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

Responsibilities:

· AI/ML Solution Development: Design, develop, and deploy AI/ML technology stacks from concept to production and deployment

· Technical Leadership: Provide technical leadership and mentorship to junior engineers, guiding them in best practices and advanced techniques.

· Develop and optimize Generative AI workflows, including prompt engineering, fine-tuning, RAG and LLM-based applications.

· Work with Large Language Models (LLMs) such as Claude, Llama, Mistral, and GPT, ensuring efficient adaptation for various use cases.

· Design and implement AI-driven automation using agentic AI systems and orchestration frameworks like Autogen, LangGraph, and CrewAI.

· Leverage cloud AI infrastructure (AWS, Azure, GCP) for scalable deployment and performance tuning.

· Collaborate with cross-functional teams to deliver AI-driven solutions.

· Front ending customer discussions, customer engagement and success stories

· Collaborate with stakeholders to gather requirements and translate them into technical specifications

Requirements

Bachelor’s in computer science, Engineering, or a related field

· Overall 5+ year’s experience in software engineering and 2+ years of experience in AI/ML, with expertise in Generative AI and LLMs. 

· Experience with AWS Bedrock or Azure OpenAI studio or similar enterprise AI environments

· Strong proficiency in Python and experience with AI/ML frameworks like PyTorch and TensorFlow

· Experience with containerization (e.g., Docker, Kubernetes), version control systems (e.g., Git) and software development methodologies (e.g., Agile, Scrum)

· Knowledge of advanced prompt engineering techniques

· Experience in AI workflow automation and model orchestration

· Hands-on experience with API development using Flask or Django

Note: Given the urgency of the role, we are currently prioritizing candidates who can join immediately or within 2-3 weeks.

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 intelligent agent systems that combine LLM-based reasoning with classical planning, search algorithms, and optimization techniques. The ideal candidate will develop robust agent architectures that operate 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 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

• 2-5 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.

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.