PeopleLogic
Website:
peoplelogic.in
Job details:
Lead the design and implementation of complex multi-step reasoning chains and
agentic RAG pipelines using LangGraph and structured output patterns.
▪ Architect and enforce safeguard mechanisms including prompt injection defence,
hallucination mitigation, and context-window management across all AI agents.
▪ Serve as the technical reference for Applied AI Engineers in Hyderabad,
conducting code reviews, mentoring on best practices, and driving engineering
standards.
▪ Integrate AI components with the Model Context Protocol (MCP) to ensure
agents access a shared, grounded knowledge base with reliable and auditable
outputs.
▪ Collaborate with Germany-based AETHER teams to embed AI services into
CI/CD pipelines, ensuring seamless deployment, observability, and compliance
with EU AI Act and DORA requirements.
▪ Continuously evaluate and optimise prompt strategies, retrieval mechanisms,
and model configurations to improve agent accuracy, latency, and reliability at
enterprise scale.
Your profile:
▪ Bachelor's or Master's degree in Computer Science, AI, or a related field, with 5+
years of hands-on experience building production AI/ML systems.
▪ Expert-level Python programming skills with deep practical experience in
LangGraph, agentic RAG architectures, and structured output design patterns.
▪ Proven ability to implement AI safety and quality mechanisms including prompt
injection defence, hallucination mitigation, and context-window management in
production environments.
▪ Strong understanding of the Model Context Protocol (MCP), LLM orchestration
patterns, and foundation models such as Anthropic Claude.
▪ Solid experience with CI/CD integration, containerisation (Docker/Kubernetes),
and DevSecOps practices in cloud environments, Any cloud experience or (GCP preferred).
Click on Apply to know more.
