The Role
Design, build, and deploy production-grade generative AI solutions, including LLM workflows, RAG pipelines, AI agents, prompt engineering, vector search, and enterprise integrations. Develop Python-based APIs and services, deploy applications on cloud platforms, and optimize accuracy, latency, scalability, reliability, and cost. Implement evaluation, guardrails, monitoring, security, and responsible AI practices while collaborating with stakeholders and technical teams.
Summary Generated by Built In
Generative AI Engineer
Experience: 4–12 Years
Location: Bengaluru
Notice Period: Immediate Joiners Only
Employment Type: Full-Time
Job Description
We are looking for a highly skilled Generative AI Engineer with hands-on experience in building and deploying production-grade GenAI solutions. The ideal candidate should have strong expertise in LLMs, RAG, Agentic AI, AI Agents, Python, prompt engineering, and vector databases.
Key Responsibilities
- Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines.
- Develop LLM workflows, AI Agents, and Agentic AI solutions.
- Work with LLMs such as OpenAI/Azure OpenAI, Claude, Gemini, Llama, or equivalent models.
- Design effective prompt engineering strategies and optimize LLM responses.
- Implement document ingestion, chunking, embeddings, retrieval, reranking, and response-generation pipelines.
- Develop APIs and AI services using Python and FastAPI/Flask.
- Work with Vector Databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search.
- Integrate GenAI solutions with enterprise data sources, applications, databases, and APIs.
- Implement LLM evaluation, guardrails, monitoring, security, and responsible AI practices.
- Deploy and manage GenAI applications on Azure, AWS, or GCP.
- Optimize AI solutions for accuracy, scalability, latency, reliability, and cost.
- Collaborate with business stakeholders, architects, data engineers, and AI teams to deliver production-ready solutions.
Required Skills
- 4–12 years of overall technology experience with strong hands-on experience in Generative AI.
- Strong programming expertise in Python.
- Hands-on experience with LLMs, RAG, Prompt Engineering, AI Agents, and Agentic AI.
- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.
- Strong understanding of embeddings, vector search, semantic search, and vector databases.
- Experience integrating LLM APIs and enterprise data sources.
- Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent AI platforms.
- Knowledge of FastAPI/Flask, REST APIs, Docker, Git, and CI/CD.
- Experience taking GenAI solutions from POC to production.
- Strong analytical, debugging, and problem-solving skills.
Good to Have
- Experience with LLMOps/MLOps and AI observability.
- Knowledge of multi-agent architectures and advanced Agentic AI frameworks.
- Experience with fine-tuning, model evaluation, hallucination reduction, and RAG optimization.
- Understanding of AI security, data privacy, governance, and responsible AI.
Requirements
Key Skills: GenAI | Generative AI | LLM | RAG | Agentic AI | AI Agents | Python | Prompt Engineering | LangChain | LangGraph | Vector Database | Azure OpenAI | AWS Bedrock | Vertex AI | LLMOps
Skills Required
- 4-12 years of overall technology experience with strong hands-on experience in Generative AI
- Strong programming expertise in Python
- Hands-on experience with LLMs, RAG, prompt engineering, AI Agents, and Agentic AI
- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks
- Strong understanding of embeddings, vector search, semantic search, and vector databases
- Experience integrating LLM APIs and enterprise data sources
- Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent AI platforms
- Knowledge of FastAPI or Flask, REST APIs, Docker, Git, and CI/CD
- Experience taking Generative AI solutions from proof of concept to production
- Strong analytical, debugging, and problem-solving skills
- Experience with LLMOps or MLOps and AI observability
- Knowledge of multi-agent architectures and advanced Agentic AI frameworks
- Experience with fine-tuning, model evaluation, hallucination reduction, and RAG optimization
- Understanding of AI security, data privacy, governance, and responsible AI
- Immediate availability to join
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Evnek Technologies is a Bengaluru-based technology and IT consulting company that helps organizations modernize through agentic and generative AI, machine learning, cloud solutions, data engineering, DevOps, and software/API development. Its services include AI-driven business transformation, autonomous intelligent agents, cloud migration and management, enterprise data capabilities, and scalable product development, with a mission to improve operational efficiency and create lasting business impact.
