Lead AI Engineer - Generative AI & Data Platforms

We are seeking a Data Engineer to design, build and optimise scalable data solutions that power analytics, business intelligence and data-driven decision making across the enterprise. This role will partner closely with data analysts, data scientists, software engineers and business stakeholders to deliver reliable, high-quality data products and modern data platforms. The ideal candidate combines strong technical expertise in data engineering with the ability to translate business needs into scalable, efficient and maintainable solutions.

Role Summary

As a Data Engineer, Specialist (AI), you will play a key technical leadership role in designing, developing, and delivering scalable AI-enabled applications, intelligent data products, and cloud-based data platforms.

This is a hands-on role for an experienced engineer with deep expertise in AI engineering, Generative AI, agentic application development, and modern data engineering. You will establish reusable solution patterns, provide technical direction, and guide engineers in delivering secure, reliable, explainable, and production-ready AI solutions.

You will bring a strong product mindset, translating complex business problems into AI and data solutions that deliver measurable outcomes. You will take end-to-end ownership across architecture, development, evaluation, deployment, observability, production reliability, and continuous improvement.

You will collaborate with Product Owners, Architects, Data Engineers, Data Scientists, Machine Learning Engineers, Risk and Governance teams, and business stakeholders to deliver solutions from concept through production.

Responsibilities

• Lead the architecture, development, and delivery of scalable Generative AI, Retrieval-Augmented Generation (RAG), agentic AI, Knowledge Graph, and AI-enabled data solutions.
• Translate business requirements into secure, scalable, and maintainable solutions using the appropriate combination of AI, data engineering, APIs, graph technologies, and deterministic software.
• Design governed, AI-ready data pipelines and reusable AI services, APIs, agent tools, retrieval components, and engineering frameworks.
• Architect secure RAG and Knowledge Graph solutions encompassing document processing, embeddings, vector and graph search, metadata, reranking, entity and relationship modeling, Graph-RAG, citations, and access controls.
• Design agentic workflows using tool and function calling, structured outputs, state and memory management, and multi-step orchestration.
• Establish AI evaluation and responsible AI practices covering groundedness, retrieval quality, hallucination, tool execution, privacy, security, guardrails, human oversight, latency, and cost.
• Define engineering and operational standards for CI/CD, automated testing, infrastructure as code, monitoring, observability, release readiness, and production support.
• Evaluate AI models, platforms, frameworks, and technical approaches based on quality, security, performance, scalability, maintainability, and cost.
• Provide technical leadership through architecture, design, and code reviews, mentoring, complex troubleshooting, and engineering guidance.
• Lead production incident resolution, root-cause analysis, preventive actions, release support, and reliability improvements for business-critical AI and data solutions.
• Drive continuous improvement through reusable engineering patterns, automation, operational learnings, and responsible use of approved AI-assisted development tools, including Claude Code and GitHub Copilot.

Qualifications and Skills

• Minimum 8 years of relevant technology experience, with significant hands-on experience in software engineering, AI engineering, machine learning engineering, or data engineering.
• Bachelor s degree in Computer Science, Information Technology, Engineering, Computer Applications, Data Science, or a related discipline from a recognized institution.
• Demonstrated experience designing and delivering AI or Generative AI applications into production.
• Strong experience architecting production-grade LLM applications using prompt and context engineering, RAG, agentic workflows, tool/function calling, structured outputs, and Model Context Protocol (MCP).
• Strong experience with AI platforms and frameworks such as Amazon Bedrock, LangChain, LangGraph, or comparable technologies.
• Hands-on experience with Knowledge Graph technologies such as Amazon Neptune, Neo4j, or similar platforms, including ontology/schema design, entity and relationship modeling, Graph-RAG, and query languages such as Gremlin, Cypher, or SPARQL.
• Advanced proficiency in Python, PySpark, Pandas, SQL, REST APIs, and secure software-engineering practices.
• Strong data engineering experience with scalable data pipelines, ETL/ELT frameworks, structured and unstructured data processing, cloud data platforms, and distributed data-processing solutions.
• Experience with technologies including AWS Glue, Amazon S3, Redshift, Athena, Spark, Databricks, Airflow/Step Functions, and Kafka/Kinesis.
• Strong experience with enterprise search and retrieval solutions using OpenSearch Serverless, vector databases, embeddings, document chunking, metadata filtering, reranking, access controls, and retrieval-evaluation techniques.
• Experience defining AI evaluation strategies encompassing groundedness, retrieval relevance, hallucination, tool execution, security, privacy, latency, cost, guardrails, and human oversight.
• Strong experience with Docker, Terraform/AWS CDK, Git, CI/CD, automated testing, monitoring, tracing, alerting, and observability.
• Demonstrated experience with production support, incident management, root-cause analysis, operational readiness, release support, and reliability improvement for AI, data, or software solutions.
• Experience using approved AI-assisted engineering tools such as Claude Code and GitHub Copilot for coding, testing, debugging, documentation, and modernization.
• Demonstrated ability to lead architecture, design, and code reviews, evaluate technical alternatives, establish reusable engineering patterns, mentor engineers, and troubleshoot complex technical issues.
• Strong product mindset with the ability to connect AI and technology decisions to meaningful business and customer outcomes.
• Ability to determine where AI is appropriate and where deterministic software or conventional data engineering represents the better solution.
• Ability to clearly explain probabilistic AI behavior, technical risks, trade-offs, and evaluation results to both technical and non-technical stakeholders.
• Strong analytical, problem-solving, debugging, and root-cause analysis capabilities.
• Experience working in Agile product environments with strong ownership, accountability, and stakeholder engagement.
• Ability to manage ambiguity, competing priorities, dependencies, and rapidly evolving AI technologies.
• Commitment to responsible AI, privacy, security, engineering excellence, and continuous learning.
• Willingness to support critical production incidents and releases outside regular working hours when needed.

Location

This role is based in Hyderabad, Telangana.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.