Silverpush
Website:
silverpush.co
Job details:
Company Description
SilverPush 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 Description
This 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 Architect
Location: 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
Click on Apply to know more.