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Tier-1 brand, metro Bangalore, and broad senior skillset (ML, DevOps, cloud) increase competition.
Deep agentic LLM specialization, evaluation pipelines, and senior ML leadership demand domain-specific experience.
Explicit 10-15 years, mandatory LLM/agentic experience, and strict tech stack make filters highly stringent.
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Design and develop production-grade Agentic AI solutions with multi-agent orchestration, backend APIs, and observability frameworks.
Lead technical delivery including AWS cloud infrastructure design, DevOps practices (CI/CD, containerization, IaC), and maintain code quality through reviews and security standards.
Mentor engineers and drive adoption of emerging Agentic AI tools and frameworks, shaping engineering standards and evaluation practices (LLM response quality, hallucination detection).
10-15 years of experience with Advanced Python (FastAPI/Flask/Django), design patterns, performance optimization, RESTful APIs, microservices, and security principles (OAuth2/JWT, OWASP).
Proficient in DevOps tools and cloud technologies: GitHub Actions/Jenkins, Docker, Kubernetes/ECS Fargate, Terraform/CDK, AWS (ECS, Lambda, S3, RDS, API Gateway, Bedrock, IAM, Secrets Manager, CloudWatch).
Experience with Agent design, multi-agent orchestration, and frameworks like LangGraph, LangChain, Agent SDKs (OpenAI/Bedrock), CrewAI/AutoGen.
Bachelor's degree in Engineering or equivalent graduation.
Experienced in leading technical architecture and delivery of complex AI/agentic workflows in cloud environments with strong Python and AWS expertise.
Demonstrates ability to implement scalable DevOps best practices, automated testing, and infrastructure as code for AI system deployments.
Skilled in mentoring and driving engineering excellence while adopting and evolving Agentic AI tooling and LLM evaluation methodologies in a corporate technology setting.