IN_Senior Associate_AI Engineer\GCC_Advisory_Bangalore(India)

Description & Summary:

We are building a world-class AI engineering capability delivering enterprise-grade intelligent applications through Generative AI and cloud-native architectures. We are seeking a Senior AI Engineer / Lead GenAI Engineer to architect and lead scalable, secure, production-ready AI solutions — bringing deep expertise in LLM-based systems, strong software and cloud engineering skills, and the ability to guide teams from design through deployment

Job Position Title:

IN_Senior Associate_AI Engineer\GCC_Advisory_Bangalore(India)

Responsibilities:

Lead the architecture, design, and implementation of enterprise-grade AI applications and intelligent workflows, leveraging LLMs, RAG, semantic search, agentic and multi-agent systems, and orchestration frameworks, MCP.

Partner with business stakeholders, product teams, and engineering leaders to translate business needs into scalable AI solution roadmaps.

Mentor engineers conduct design and code reviews and elevate the overall engineering maturity of the AI team.

Stay current with the evolving AI ecosystem and guide adoption of relevant tools, frameworks, and best practices.

Mandatory skill sets:

AI/ML Architecture: 5–9 years of software architecture and distributed system design experience, including 3+ years of designing production-grade AI/ML solutions.

Generative AI Engineering: Strong in Python and proven hands-on experience building production LLM applications using frameworks like LangChain, LangGraph, LlamaIndex, or agentic workflows (CrewAI, AutoGen, Semantic Kernel) integrated with RAG, MCP. Strong RAG experience — vector DBs, chunking, embedding, semantic search.

Multi-Platform LLM Experience: Hands-on experience across multiple AI platforms such as Azure OpenAI, OpenAI, Anthropic Claude, Google Vertex AI/Gemini, or AWS Bedrock.

AI Evaluation & Observability: Experience with evaluation-driven development and observability tools such as LangSmith, RAGAS, or DeepEval, along with responsible AI and guardrail & security practices.

Cloud-Native Engineering: Strong hands-on experience with Azure or AWS or GCP, including containerization, CI/CD, Kubernetes, Helm charts and production deployment of scalable AI applications.

Financial Services Context: Familiarity with BFSI compliance frameworks (GDPR, DORA, Basel III/IV) and exposure to use cases such as payments, trade finance, or lending workflows.

Leadership & Communication: Strong stakeholder communication skills with the ability to mentor engineers and translate business goals into scalable, measurable AI solutions.

Preferred skill sets:

NA

Years of experience required:

4 to 7 years of overall experience, including 3+ years specializing in AI/ML solutioning.

Education qualification:

BE / B.Tech / MCA / M.Tech / MBA