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Lead Backend AI Engineer

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Remote

Lead Backend AI Engineer

Netweb Software

Lead Backend AI Engineer

Skills

PythonGolangMicroservicesNeo4jAIAWS

16 days ago

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Important information


Contract type:

Permanent

Location:

Vadodara, Gujarat, India

Work mode:

Remote

Published on:

9 October 2026

What they need


NetWeb Software is Hiring: Lead Backend AI Engineer
Location: Remote
Experience: 8+Years

Drop your CV to [email protected]

We are looking for a Lead Backend AI Engineer to design and build scalable, secure, and production-ready Agentic AI platforms for enterprise IT and SecOps automation.

Key Responsibilities & Required Skills
* Strong expertise in Golang and Python, including concurrency, asynchronous programming, microservices, and distributed systems.
* Hands-on experience building multi-agent AI systems using LangGraph, LangChain, Semantic Kernel, LlamaIndex, or custom agent frameworks.
* Experience with agent orchestration, state management, tool calling, durable workflows, and failure recovery.
* Practical experience in LLM fine-tuning (LoRA/QLoRA, DPO), Hugging Face PEFT/TRL, and open-weight models.
* Production experience with LLM inference and serving using vLLM, TensorRT-LLM, or Ollama, including model quantization.
* Strong understanding of RAG, GraphRAG, hybrid search, embeddings, reranking, vector databases (Qdrant, Milvus, pgvector), and graph databases (Neo4j/AWS Neptune).
* Experience implementing AI safety guardrails, sandboxed execution, dry-run validation, rollback mechanisms, and secure tool execution.
* Hands-on experience with automated AI evaluation using DeepEval, Ragas, or promptfoo, including CI/CD-integrated regression testing.
* Knowledge of enterprise infrastructure integrations, REST APIs, SSH/CLI automation, SNMP, gNMI, and OpenTelemetry.

Preferred Skills: OpenClaw, Browser-Use, NETCONF, gRPC, model distillation, and experience with Llama, Mistral, Qwen, or DeepSeek models.

Education: BE/ME in IT or Computer Engineering, MCA, MSc-IT, BCA, or equivalent qualification.

Candidates should demonstrate strong system design, technical leadership, problem-solving, communication, and the ability to build reliable AI systems for production environments.

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