Jr. Gen AI Engineer

18 hours ago

Noida, Uttar Pradesh, India Source-Right Full time

Position: Jr. Gen AI Engineer (CE45SF RM 3817)
**Must have skills : Gen AI, Python or JAVA, Vector DB, LLM, RAG, Linux OS fundamentals

Good to have : Communication, Network firewalls, routers and switches, Spring boot
Role: Gen AI Engineer – LLM Architecture, RAG, and Agentic AI
Requirements**

  • 4-5 years of relevant experience in AI/ML or backend systems, with a strong focus on LLM application development and AI system design.
  • Proven experience architecting and deploying AI frameworks or agentic systems in production environments.
  • Strong expertise in AI framework and the Java ecosystem — comfortable building and orchestrating
  • AI workflows using Spring Boot, Spring AI, and vector storage integrations.
  • Experience in RAG architecture, prompt engineering, memory management, and model orchestration patterns.
  • Familiarity with OpenAI, Anthropic, and Google Gemini APIs and evaluation frameworks for reasoning quality.
  • Strong software engineering fundamentals — versioning, pipelines, CI/CD, and API integration.
  • Experience with vector databases (e.g., Pinecone, Weaviate, or Chroma) or knowledge graph-based retrieval.

Responsibilities

  • Architect and build Cognia's AI framework, integrating LLMs, memory, RAG, and agentic reasoning across the platform.
  • Design AI agents and reasoning flows that interpret app, infra, and IAM telemetry for risk triage and remediation.
  • Develop retrieval-augmented generation (RAG) pipelines for context-based summarization, persona-driven views, and continuous learning.
  • Implement LLM memory and context management (short-term, long-term, and episodic memory) for persistent reasoning.
  • Tune prompts, evaluation logic, and reasoning paths across multiple models (GPT-4, Claude, Gemini, etc.).
  • Collaborate with founders, backend engineers, and data teams to integrate AI logic with product pipelines and APIs.
  • Define AI architecture standards, evaluation metrics, and observability for all LLM-driven components.

Bonus
Background in cybersecurity, SaaS platforms, or risk intelligence systems.

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