Lead AI Engineer

Lead AI Engineer – LLM & Agentic AI Systems

Location: Bengaluru

Experience: 4–6 Years

Department: Engineering – AI/ML

Employment: Full-Time

About LeadSquared

LeadSquared is a leading sales execution and marketing automation platform trusted by 2,000+ businesses globally, including healthcare, education, financial services, and real estate. Headquartered in Bengaluru with offices across the US, UK, UAE, and Southeast Asia, we empower sales teams to close faster, smarter, and at scale.

Our AI team is at the forefront of integrating cutting-edge Large Language Model capabilities into enterprise workflows — building intelligent agents, copilots, and automation systems that redefine how businesses operate.

Role Overview

We are looking for a hands-on Lead AI Engineer with strong experience in building and deploying LLM-powered applications and Agentic AI systems. The role involves designing scalable AI architectures, developing autonomous agents, and driving end-to-end implementation of intelligent workflows.

The ideal candidate should have strong backend engineering skills, expertise in Python, and practical experience with LLMs, RAG pipelines, multi-agent orchestration and production-grade AI applications. The candidate will also contribute to technical decisions, mentor engineers and drive engineering best practices.

Key Responsibilities

• Design, develop and deploy LLM-powered agentic systems using frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen or CrewAI.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases such as Pinecone, Weaviate, Chroma and pgvector.
• Develop multi-agent orchestration systems with tool calling, function calling and integrations with internal APIs, databases and third-party services.
• Drive prompt engineering, structured output generation and context management to improve AI reliability and performance.
• Design evaluation frameworks and observability pipelines to monitor agent performance, accuracy, latency and cost.
• Lead backend development using Python, building scalable APIs, microservices and asynchronous AI pipelines.
• Optimise LLM inference for latency and cost through caching, batching, quantisation and model selection.
• Work closely with Product and Engineering teams to translate business requirements into scalable AI solutions.
• Take ownership of technical architecture, code quality, production deployments and system performance.
• Mentor engineers, conduct code reviews and establish engineering best practices.

Required Qualifications

Experience

• 4–6 years of overall software engineering experience.
• Strong hands-on experience building and deploying LLM-based applications and Agentic AI systems.
• Proven experience taking AI solutions from development to production.

Technical Skills

• Strong proficiency in Python and backend development.
• Hands-on experience with LLM APIs such as OpenAI, Anthropic, Gemini or open-source models like Llama and Mistral.
• Experience with agentic frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen or CrewAI.
• Strong understanding of RAG architectures, embeddings, semantic search and vector databases.
• Experience building multi-agent systems, tool calling and function calling.
• Strong understanding of REST APIs, microservices, asynchronous programming and system design.
• Experience with Docker, Kubernetes and cloud platforms such as AWS, GCP or Azure.

Problem-Solving & Engineering Mindset

• Strong problem-solving and architectural design capabilities.
• Ability to independently drive technical initiatives and solve complex engineering challenges.
• Experience with LLM evaluation, prompt debugging and performance optimisation.
• Strong ownership mindset with the ability to guide and mentor engineering teams.

Preferred Qualifications

• Experience with multi-agent orchestration and agent memory systems.
• Familiarity with fine-tuning, model adaptation or RLHF workflows.
• Background in NLP, information retrieval or conversational AI.
• Prior experience in B2B SaaS or CRM domains.
• Experience with AI/ML cloud services and production-scale AI deployments.
• Contributions to open-source AI/ML projects or published technical research.

What We Are Looking For

A hands-on AI engineering professional who can drive architecture and development, contribute through coding, solve complex AI challenges and take ownership of building scalable, production-ready Agentic AI solutions.