CRISIL
Website:
crisil.com
Job details:
# Senior Lead Generative AI Engineer (Individual Contributor)
## Role Summary
We are hiring a senior individual contributor to design, build, and productionize end-to-end agentic AI systems for high-impact enterprise workflows. This role is for a hands-on builder who can own architecture, coding, evaluation, reliability, and deployment at scale.
You will work on complex AI programming problems that require deep engineering judgment across multi-agent orchestration, MCP integrations, secure tool usage, retrieval systems, and cloud deployment.
## Why This Role Is Different
- You will own the full lifecycle: problem framing, architecture, implementation, deployment, observability, and continuous optimization.
- You will work on hard, real-world AI systems where accuracy, latency, reliability, and governance matter together.
- You will influence engineering quality standards across agent design, LLMOps, and production guardrails while remaining a strong individual contributor.
## Core Responsibilities
- Build end-to-end agentic AI systems from scratch using robust software engineering and AI systems design principles.
- Design and implement multi-agent workflows (planner, executor, reviewer, verifier, fallback) with clear control flows and reliability mechanisms.
- Build and integrate MCP-compatible tool ecosystems, including secure access controls, tool permissioning, and auditable execution patterns.
- Architect and optimize RAG pipelines with vector databases, structured retrieval, reranking, and context management.
- Define and enforce output quality standards using schema-driven generation, validation layers, and guardrails.
- Establish evaluation pipelines for correctness, groundedness, robustness, cost, and latency.
- Lead cloud-native deployment and runtime optimization on AWS or Azure, including scalable inference and operational monitoring.
- Drive incident triage and production debugging for agentic workflows.
- Translate business goals into AI system designs with measurable outcomes.
- Mentor junior engineers through design reviews, code reviews, and problem decomposition.
## Must-Have Technical Skills
- 9 to 12 years of software engineering experience with advanced Python expertise.
- Strong command of software design patterns and architecture for complex distributed systems.
- Working depth in deep learning foundations: neural networks, transformers, embeddings, and modern LLM behavior.
- Proven experience building and shipping production agentic AI systems, not only prototypes.
- Proven experience with multi-agent orchestration frameworks and patterns.
- Proven experience implementing MCP server-client integrations in secure enterprise contexts.
- Strong RAG engineering skills with vector databases and retrieval quality tuning.
- Hands-on LLMOps capability: experiment tracking, evaluation frameworks, model monitoring, and release governance.
- Strong prompt, context, and harness engineering capability for high-fidelity outputs.
- Strong understanding of data security and governance controls for AI systems.
## Preferred Skills
- Proficiency in additional programming languages beyond Python.
- Experience with advanced inference optimization (for example multi-GPU sharding, quantization, hardware-specific runtimes).
- Experience with enterprise integration patterns across APIs, data platforms, and workflow systems.
- Experience with financial or document-intelligence style structured extraction systems.
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