Experience: 6 - 10 + Years

Locations: Chennai / Bangalore / Hyderabad

Employment Type: Full Time

Job Summary

We are looking for experienced Generative AI professionals to design, develop, architect, and deploy enterprise-grade AI solutions. The role is suitable for candidates with strong hands-on experience in GenAI, LLMs, RAG, Agentic AI, Python, AI application development, cloud platforms, and production AI deployments.

Depending on experience and expertise, candidates may be considered for GenAI Engineer, Senior GenAI Engineer, GenAI Lead, AI Architect, or Forward Deployed Engineer (FDE) positions.

The role involves working closely with engineering teams, business stakeholders, and customers to identify AI use cases, rapidly prototype solutions, and take them through production deployment.

Key Responsibilities

- Design, build, architect, and integrate Generative AI and LLM-based solutions using Python and modern AI frameworks.
- Develop enterprise-grade RAG pipelines, including document ingestion, chunking, embeddings, retrieval, reranking, context management, and LLM response generation.
- Design and develop Agentic AI solutions, including AI agents, multi-agent workflows, orchestration, tool calling, MCP, memory, and human-in-the-loop capabilities.
- Build scalable and production-ready GenAI/AI-ML applications and services using Python and relevant frameworks.
- Work with LangChain and/or similar GenAI frameworks, LLMs, prompt engineering, vector databases, semantic search, and knowledge retrieval technologies.
- Design and implement Forward Deployed AI solutions, working directly with business and engineering teams to identify use cases, rapidly prototype solutions, and deploy AI capabilities into real-world environments.
- Develop intelligent document processing and document ingestion pipelines for enterprise use cases.
- Work with GraphRAG, Knowledge Graphs, semantic search, and vector databases where applicable.




- Develop responsive and user-friendly GenAI application interfaces using React, Angular, or similar technologies.
- Design, deploy, and scale AI solutions on one or more major cloud platforms such as Microsoft Azure, AWS, or GCP.
- Work with Azure AI/ML services, cloud AI services, Kubernetes, APIs, and distributed systems.
- Implement MLOps / LLMOps capabilities covering model lifecycle, deployment, monitoring, governance, explainability, and production readiness.
- Design and implement scalable data architectures, APIs, event-driven systems, and high-volume data processing pipelines.
- Collaborate with product, engineering, data, and business teams to translate business problems into scalable AI solutions.
- Define AI technical strategies, reference architectures, engineering standards, and best practices for senior-level positions.
- Engage directly with business leaders, executives, and customers to understand requirements and drive AI solution delivery.
- Mentor engineers and contribute to technical direction and engineering excellence.
- Own AI solutions end-to-end from problem definition and prototyping through production deployment and optimization.

Required Technical Skills

GenAI / LLM

- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- RAG
- Advanced RAG
- Agentic AI
- AI Agents
- Multi-Agent Systems
- Tool Calling / Function Calling
- MCP
- LLM orchestration

AI / Search / Data

- Vector Databases
- Embeddings
- Semantic Search
- Reranking
- Knowledge Graphs
- GraphRAG
- Intelligent Document Processing
- Document ingestion pipelines





Programming / Application Development

- Strong Python programming
- REST APIs / backend development
- Full-stack AI application development
- React and/or Angular
- Microservices and scalable application development

Cloud / Infrastructure

- Microsoft Azure and/or AWS and/or GCP
- Azure AI / ML services
- Kubernetes
- Cloud-native application development
- CI/CD

MLOps / LLMOps

- Model deployment and lifecycle management
- AI/LLM monitoring
- Governance
- Model evaluation
- Production readiness
- Observability

ML

- Machine Learning fundamentals
- Forecasting
- Prediction
- Anomaly Detection
- Fraud / analytics use cases

Experience

- Forward Deployed Engineer : 6 - 10 years
- GenAI Engineer : 6 + years
- GenAI Lead : 10+ years

Candidates with strong hands-on GeAI experience and experience taking AI solutions into production are preferred.

Preferred Experience

- Experience working in finance, banking, healthcare, or other regulated environments.
- Experience working directly with customers/business stakeholders in a consulting or Forward Deployed Engineering environment.
- Experience defining AI strategy, roadmaps, reference architectures, and technical standards.
- Strong stakeholder management and communication skills.
- Ability to work independently and own initiatives end-to-end with minimal supervision.

Key Competencies

- Generative AI & LLMs
- RAG / GraphRAG
- Agentic AI
- AI Application Development
- Python
- Cloud AI
- Vector Databases
- Knowledge Graphs
- MLOps / LLMOps
- Data Architecture
- Full-Stack Development
- Solution Architecture
- Customer / Stakeholder Management
- Technical Leadership
- Problem Solving

Why Join Opportunity to work on enterprise-scale Generative AI, Agentic AI, RAG, intelligent automation, and AI platform initiatives, with exposure to contemporary cloud, AI, data, and software engineering technologies. Role & responsibilities

📌 GenAI Lead / GenAI Engineer / Forward Deployed Engineer (FDE) (Chennai)
🏢 Workiy Technologies
📍 Chennai