Senior Technical Lead

Job Summary

Role Overview

We are seeking an Agentic AI Engineer to design, build, and deploy autonomous, goal-driven AI systems (“AI agents”) that can reason, plan, take actions, and collaborate with other systems and agents.

The role focuses on LLM-powered multi-agent architectures, tool use, memory, orchestration, and real-world integration to solve complex business problems at scale.

Key Responsibilities

Key Responsibilities

Agentic System Design & Development

• Design and implement autonomous AI agents using Large Language Models (LLMs)

• Build single-agent and multi-agent systems with planning, reasoning, memory, and tool execution

• Implement agent behaviors such as:

Task decomposition and planning

• Reflection and self-correction

• Long-term and short-term memory

• Collaboration and delegation across agents

LLM & AI Engineering

• Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Anthropic, open-source models)

• Apply prompt engineering, structured outputs, function calling, and RAG techniques

• Fine-tune or adapt foundation models where required

• Evaluate and improve model performance, reliability, and hallucination control

Tooling & Orchestration

• Enable agents to safely use tools such as:

APIs and microservices

• Databases (SQL/NoSQL/vector stores)

• Web search and enterprise systems

• Implement agent frameworks and orchestration layers (e.g., Lang Graph, CrewAI, Auto Gen, custom frameworks)

Data, Memory & Knowledge Systems

• Design vector-based memory systems using embeddings

• Implement Retrieval-Augmented Generation (RAG) pipelines

• Manage knowledge ingestion, indexing, and lifecycle

Production & Engineering Excellence

• Build scalable, reliable, and secure AI services

• Collaborate with product, platform, and data engineering teams

• Implement monitoring, logging, evaluation, and safety guardrails

• Ensure compliance with data privacy and responsible AI standards

Skill Requirements

Required Skills & Qualifications

Core Technical Skills

• Strong programming skills in Python (mandatory); JavaScript/TypeScript is a plus

• Hands-on experience building applications with LLMs

• Deep understanding of:

Agentic workflows and autonomous systems

• Prompting strategies and output control

• RAG architectures and vector databases

AI & ML Knowledge

• Working knowledge of:

Transformer-based models

• Embeddings and semantic search

• Model evaluation and bias mitigation

• Familiarity with fine-tuning and inference optimization

Systems & Cloud

• Experience with cloud platforms (Azure preferred, AWS/GCP acceptable)

• APIs, microservices, and serverless architectures

• CI/CD, containerization (Docker), and basic MLOps practices

Other Requirements

Preferred / Nice-to-Have Skills

• Experience with agent frameworks (Lang Chain, Lang Graph, Auto Gen, CrewAI, Semantic Kernel)

• Knowledge of reinforcement learning or planning algorithms

• Experience in enterprise AI adoption or AI governance

• Front-end integration for AI-driven UX (optional)

--- ## Soft Skills

• Strong problem-solving and system design skills

• Ability to translate business problems into autonomous AI workflows

• Clear communicator with a collaborative mindset

• Comfort working in fast-evolving, ambiguous problem spaces