Gen AI Engineer

1 day ago

Hyderabad, Telangana, India InfoVision Inc. Full time
We are seeking a highly experienced Senior Generative AI Expert to lead initiatives in building and deploying GenAI solutions. The ideal candidate should possess strong proficiency in Python, hands-on experience with frameworks such as LangChain, LlamaIndex, and the ability to work with both open-source (e.g., LLaMA, Gemma, Mistral, Falcon) and proprietary LLMs (e.g., OpenAI, Anthropic, Gemini). The candidate should be well-versed in the full lifecycle of GenAI applications — from prompt engineering to fine-tuning and production deployment.

Experience : 6 years to 8 years

Location : Chennai /Hyderabad / Bangalore

Key Responsibilities:

- Lead the design and development of GenAI applications using frameworks like LangChain, LlamaIndex, and others.
- Evaluate and integrate both open-source and proprietary LLMs based on project needs.
- Build agentic systems and retrieval-augmented generation (RAG) pipelines.
- Collaborate with data engineers, backend developers, and product teams to deploy AI models into production.
- Fine-tune pre-trained language models on domain-specific tasks.
- Drive research-to-production pipelines by implementing the latest advancements in LLMs, transformers, embeddings, and vector databases.
- Mentor junior AI engineers and contribute to internal knowledge sharing.
- Optimize model performance, latency, and accuracy across various use cases.

Required Skills & Qualifications:

- 6+ years of experience in software/ML engineering, with 2+ years specifically in GenAI/LLM space.
- Strong expertise in Python and popular GenAI libraries (LangChain, LlamaIndex, HuggingFace Transformers, etc.)
- Deep understanding of LLMs, prompt engineering, embeddings, vector stores (e.g., FAISS, Pinecone, Weaviate).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Familiarity with fine-tuning, quantization (e.g., LoRA, QLoRA), and inference optimization.
- Ability to work autonomously and lead cross-functional teams.
- Strong communication, system design, and leadership skills.

Preferred Qualifications:

- Prior experience with multi-agent systems, memory-based agents, or tools like CrewAI, AutoGen, LangGraph.
- Familiar with MCP (Model Context Protocol) and how to implement it in agentic ai applications.
- Knowledge of multimodal models (text-to-image/video/audio).
- Publications or contributions in the field of NLP or GenAI.
- Open-source contributions in the LLM ecosystem.

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