Principal Applied AI Engineer

Role & responsibilities

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.

Preferred candidate 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 (GCP preferred).

Nice-to-have: Experience in regulated industries (financial services, EU AI Act,

DORA), familiarity with GitHub Actions and enterprise-scale repository

ecosystems, German language skills.