Senior AI Engineer - Multi Level Orchestration
- Source: Naukri
- Hucon Solutions
- On-site
- Hyderabad
- Full-Time
- Senior
Job Description
- Your responsibilities:
Architect and implement multi-agent orchestration patterns using LangGraph, designing skills-based workflows that power the Refinement, Decision, and Coding Agents across the Agent Chain platform. - Design and evolve prompting architectures and RAG strategies that achieve high- fidelity, reliable AI outputs grounded in application-specific knowledge bases via Model Context Protocol (MCP).
- Conduct technical design reviews and establish engineering best practices for AI service development, ensuring compliance with EU AI Act, DORA, and internal DevSecOps standards.
- Mentor junior AI engineers in the Hyderabad team on prompt engineering techniques, agentic design patterns, and production-quality Python development.
- Collaborate closely with Germany-based architects and product owners to translate architectural concepts into functional, scalable AI services integrated with GitHub EU Cloud and Jira workflows.
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Evaluate and benchmark foundation models (Claude, GPT, Gemini) for specific agent tasks, optimising for accuracy, latency, and cost across the agent pipeline.
- Your profile:
Bachelor’s or Master’s degree in Computer Science, AI, or a related field, with 5+ years of experience building AI/ML systems and at least 2 years working with LLM- based applications in production. - Expert-level Python programming skills with hands-on experience in LangGraph, LangChain, and modern AI orchestration frameworks for building multi-agent systems.
- Deep expertise in prompt engineering, RAG architectures, and agentic workflow design, with a proven track record of delivering high-quality, reliable AI outputs at scale.
- Strong working knowledge of foundation models (Anthropic Claude, OpenAI GPT, Google Gemini) including fine-tuning strategies, context window management, and model evaluation methodologies.
- Demonstrated ability to lead technical discussions, and drive engineering standards within a distributed, cross-timezone team.
- Nice-to-have: Experience with Model Context Protocol (MCP), DevSecOps toolchains (GitHub Actions, Terraform, Kubernetes), regulated financial environments
Skills
- LangGraph
- Python
- Github
- JIRA
- benchmark
- claude-by-anthropic
- Gemini
- LangChain
- openai
- github-actions
- Terraform
- Kubernetes
