N
Naukri Assist
Forward Deployed Engineers Gen AI+Agentic AI
Skills
Google Cloud PlatformDockerPythonData ScienceMicroservicesPyTorchTensorFlowMachine LearningAIAWSKubernetesAzure
1 month ago
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Important information
Contract type:
Permanent
Salary:
₹3,000,000 – ₹7,000,000 / year
Location:
Delhi, India
Work mode:
Onsite
Published on:
21 September 2026
What they need
Key Responsibilities
- Design, develop, and deploy enterprise AI solutions leveraging Generative AI, Agentic AI, LLMs, SLMs, and RAG.
- Work closely with customers to understand business problems and translate them into scalable AI solutions.
- Develop AI-powered applications for conversational AI, intelligent automation, and AI-assisted Software Development Lifecycle (SDLC).
- Build production-ready AI workflows using LangGraph, CrewAI, LangChain, Azure AI Foundry, AWS Bedrock, Google Gemini Enterprise, and similar AI platforms.
- Design agent orchestration frameworks integrating enterprise systems, APIs, databases, and external tools.
- Optimize AI solutions for accuracy, latency, scalability, reliability, and cost efficiency.
- Build robust APIs, microservices, and AI services following software engineering best practices.
- Collaborate with Product, Engineering, Data Science, and DevOps teams to deliver enterprise AI platforms.
- Participate in customer workshops, solution design, PoCs, technical discussions, and deployment activities.
- Contribute to continuous improvement by evaluating emerging AI technologies and recommending innovative solutions.
Required Skills & Qualifications
- 5–13 years of experience in Software Engineering, AI Engineering, or Machine Learning.
- Strong programming expertise in Python.
- Hands-on experience with LLMs, Agentic AI, Generative AI, RAG, Prompt Engineering, and AI Agents.
- Experience with AI frameworks such as LangGraph, LangChain, CrewAI, LlamaIndex, or similar orchestration platforms.
- Knowledge of AWS Bedrock, Azure AI Foundry, Google Gemini Enterprise, or equivalent AI platforms.
- Experience with PyTorch, TensorFlow, Hugging Face, or modern AI frameworks.
- Strong understanding of vector databases, embeddings, semantic search, and AI workflows.
- Experience with Docker, Kubernetes, REST APIs, CI/CD, and cloud platforms (AWS, Azure, or GCP).
- Strong communication skills with experience working directly with enterprise clients.
- Experience working in Agile development environments.
Preferred Skills
- Experience with MLOps/LLMOps and AI deployment frameworks.
- Exposure to PEFT, LoRA, QLoRA, or model optimization techniques.
- Knowledge of distributed computing and enterprise AI infrastructure.
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