Lead Engineer - AI

Company DescriptionSilverPush is an advertising technology firm providing AI-Powered contextual solutions. It helps brands and agencies target relevant audiences in the cookieless world without meddling with their privacy. We have clients who we have worked with such as Ford, Nestle, Coca-Cola, Samsung, etc. Silverpush operates in 20+ countries across Southeast Asia, the Middle East, Africa, the USA, the UK, and India. The company has won 7+ global awards, worked with Fortune 500 brands, and has completed 4000+ campaigns. Silverpush is rapidly growing!Role DescriptionThis is a full-time on-site role located in Gurgaon for Lead Engineer - AI. The role involves leading the design and development of AI-powered solutions, implementing machine learning algorithms, and managing projects from prototype to deployment. Responsibilities include collaborating with cross-functional teams, staying updated on the latest advancements in AI, ensuring scalable and efficient code, and solving complex technical challenges to enhance the company’s advertising solutions.Job Title: Lead AI Engineer / AI Systems ArchitectLocation: GurugramExperience: 5+ yearsAbout the RoleWe 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 ResponsibilitiesArchitect 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 & TechnologiesCore AI & ML:Expertise in working with LLMs (OpenAI GPT, Anthropic Claude, Llama, Mistral, Gemini, etc.)Strong understanding of prompt engineering, function calling, and context managementExperience with LangChain, LangGraph, and MCP (Model Context Protocol) for building complex AI workflowsSolid grasp of RAG architecture, vector databases (Elastic Search, Pinecone, Weaviate, Chroma), and embedding modelsFamiliarity 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 processingCloud and deployment knowledge (AWS, GCP, Azure, or serverless environments)Databases: MongoDB / PostgreSQL / RedisStrong understanding of API design, security, and scalabilityOptimization & Observability:Experience in latency reduction, load balancing, and caching strategiesToken usage optimization and cost control for LLM-based applicationsMonitoring, 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 systemsSecurity and AI safety guardrailsWhat You’ll Bring5+ years of experience in AI/ML system design, development, and deploymentStrong background in NLP, generative AI, or applied machine learningAbility to balance innovation with performance and scalabilitySolid understanding of modern software engineering best practicesA builder’s mindset — curious, hands-on, and driven to create impact through intelligent systemsWhy Join UsWork across a diverse portfolio of AI initiatives, from chatbots to multimodal systemsCollaborate with a team pushing the boundaries of AI-first product developmentShape the future of how humans interact with intelligent systemsFlexible, fast-paced, innovation-driven environment

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