Feuji - Senior Generative AI Engineer - LLM/RAG

5 days ago

Hyderabad, Telangana, India hirist Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Note : If shortlisted, you will be invited for initial rounds on 8th November'25 (Saturday) in Hyderabad


Description :

Role : Senior GenAI Engineer

Company : Feuji Software Solutions Pvt Ltd.,

Mode of Hire : Permanent Position

Experience : 6 to 10 Years

Work Location : Hyderabad

About Feuji :

Feuji, established in 2014 and headquartered in Dallas, Texas, has rapidly emerged as a leading global technology services provider

With strategic locations including a Near Shore facility in San Jose, Costa Rica, and Offshore Delivery Centers in Hyderabad, and Bangalore, we are well-positioned to cater to a diverse clientele. Our team of 600 talented engineers drives our success, delivering innovative solutions to our clients and contributing to our recognition as a 'Best Place to Work For.'

We collaborate with a wide range of clients, from startups to industry giants in sectors like Healthcare, Education, IT, and engineering, enabling transformative changes in their operations. Through partnerships with top technology providers such as AWS, Checkpoint, Gurukul, CoreStack, Splunk, and Micro Focus, we empower our clients' growth and innovation.

With a clientele including Microsoft, HP, GSK, and DXC Technologies, we specialize in managed cloud services, cybersecurity, Product and Quality Engineering Services, and Data and Insights solutions, tailored to drive tangible business outcomes.

Our commitment to creating 'Happy Teams' underscores our values and dedication to positive impact. Feuji welcomes exceptional talent to join our team, offering a platform for growth, development, and a culture of innovation and excellence.

About the Role :

Designs and develops advanced LLM-powered and multi-agent applications leveraging RAG, prompt engineering, and fine-tuning techniques like LoRA and RLHF. Builds LLMOps pipelines for model evaluation, deployment, and monitoring using frameworks like LangChain, LangGraph, and LangSmith. Implements MCP/A2A protocols, guardrails, and vector-based retrieval systems to ensure safe, efficient, and scalable GenAI solutions.

Key Responsibilities :

GenAI Application Development :

- Build production LLM applications (GPT-4, Claude, Gemini, Llama, Mistral).

- Design RAG systems: semantic search, chunking, reranking, hybrid retrieval.

- Develop multi-agent systems, function calling, and agentic workflows.

- Implement advanced prompt engineering (zero-shot, few-shot, CoT, ReAct).

LLM Fine-Tuning & Optimization :

- Fine-tune LLMs using LoRA, QLoRA, PEFT, instruction tuning, RLHF, DPO.

- Optimize inference: quantization, pruning, distillation, caching.

LLMOps & Orchestration :

- Build end-to-end LLM pipelines: versioning, evaluation, deployment, monitoring.

- Orchestrate workflows using LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel.

- Implement MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols.

- Multi-LLM routing, semantic caching, and cost optimization.

Vector Search & Embeddings

- Build vector databases (Pinecone / FAISS / Chroma DB etc.).

- Design embedding pipelines (OpenAI, Cohere, sentence-transformers).

Safety & Monitoring :

- Implement guardrails: content moderation, prompt injection prevention, PII detection.

- Build evaluation frameworks with LLM-as-judge and human feedback loops.

- Monitor via LangSmith, Phoenix, Arize: latency, cost, quality, hallucinations.

Required Skills :

- Strong hands-on experience with an ability to lead a team

GenAI Core :

- Transformers, foundation models, prompt engineering, RAG, fine-tuning (LoRA, RLHF).

- LangChain, LangGraph, LangSmith, LlamaIndex, CrewAI, AutoGen.

- MCP and A2A protocol implementation.

- Vector DBs (Pinecone / FAISS / Chroma DB etc.).

- LLM serving (vLLM, TGI, Triton, LiteLLM).

- Guardrails AI, NeMo Guardrails, Llama Guard.

ML & Engineering :

- Python, PyTorch, Transformers (Hugging Face).

- API design (FastAPI), Docker, Kubernetes.

- Cloud: AWS Bedrock, GCP Vertex AI, Azure OpenAI.

Data :

- Document processing, ETL, SQL/NoSQL.

- Data privacy compliance (GDPR, HIPAA).

Nice to Have Skills :

- Multi-modal AI (GPT-4V, CLIP), code generation (Codex, CodeLlama).

- Distributed training (DeepSpeed, Ray), compression (GPTQ, AWQ).

- On-device deployment , ONNX).

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