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SilverEdge Technologies Private Limitedvia Indeed
Lead Engineer - AI
REMOTEPosted 2mo ago
NLP / LLMLead#python#huggingface#langchain#llm#gpt#nlp#aws#gcp#azure#mlflow
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About the Role
Job Title: Lead AI Engineer / AI Systems Architect
Location: Remote / Hybrid (Gurugram)
Experience: 5+ years
About the Role
We are looking for an experienced Lead AI Engineer who can architect, build, and deploy scalable AI-driven systems across a variety of use cases — from generative AI applications to intelligent automation and recommendation systems.
You will be responsible for designing and optimizing end-to-end AI pipelines that combine large language models (LLMs), retrieval systems, and custom logic to deliver robust and efficient AI solutions.
Key Responsibilities
- Architect and implement LLM-powered systems, including prompt orchestration, function calling, and context management.
- Design and maintain modular AI pipelines integrating retrieval, reasoning, and response generation layers.
- Work on AI toolchains and frameworks such as LangChain, LangGraph, and Model Context Protocol (MCP) for model orchestration and agent workflows.
- Develop scalable backend APIs and microservices to expose AI capabilities.
- Integrate vector databases, embedding models, and retrieval-augmented generation (RAG) pipelines.
- Evaluate, fine-tune, and deploy open-source or proprietary models (text, image, or multimodal).
- Ensure performance optimization, including latency reduction, caching, token management, and cost optimization.
- Collaborate with data, backend, and frontend teams to embed AI features across multiple products.
- Build internal tools and frameworks to accelerate experimentation and model deployment.
- Stay current with emerging AI technologies, frameworks, and research to guide product direction.
Essential Skills & Technologies
Core AI & ML:
- Expertise in working with LLMs (OpenAI GPT, Anthropic Claude, Llama, Mistral, Gemini, etc.)
- Strong understanding of prompt engineering, function calling, and context management
- Experience with LangChain, LangGraph, and MCP (Model Context Protocol) for building complex AI workflows
- Solid grasp of RAG architecture, vector databases (Elastic Search, Pinecone, Weaviate, Chroma), and embedding models
- Familiarity with fine-tuning and model serving (using Hugging Face, vLLM, Ollama, etc.)
Engineering & Architecture:
- Strong proficiency in Python (FastAPI preferred)
- Deep experience in microservices, event-driven systems, and async processing
- Cloud and deployment knowledge (AWS, GCP, Azure, or serverless environments)
- Databases: MongoDB / PostgreSQL / Redis
- Strong understanding of API design, security, and scalability
Optimization & Observability:
- Experience in latency reduction, load balancing, and caching strategies
- Token usage optimization and cost control for LLM-based applications
- Monitoring, logging, and tracing (New Relic, ELK)
Additional Plus:
- Experience designing AI workflows or agent-based systems (preferred)
- Strong understanding of model evaluation, experimentation, and MLOps practices (experience with tools such as MLflow, Kubeflow, Weights & Biases or similar is a plus)
- Understanding of multimodal AI (image, speech, video, or sensor data)
- Real-time streaming systems
- Security and AI safety guardrails
What You’ll Bring
- 5+ years of experience in AI/ML system design, development, and deployment
- Strong background in NLP, generative AI, or applied machine learning
- Ability to balance innovation with performance and scalability
- Solid understanding of modern software engineering best practices
- A builder’s mindset — curious, hands-on, and driven to create impact through intelligent systems
Why Join Us
- Work across a diverse portfolio of AI initiatives, from chatbots to multimodal systems
- Collaborate with a team pushing the boundaries of AI-first product development
- Shape the future of how humans interact with intelligent systems
Flexible, fast-paced, innovation-driven environment
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