Senior Technical Lead – Agentic AI, Generative AI

This is a fully remote position, open to applicants in India.

📋 Description

• Design and develop Agentic AI and Generative AI systems from initial concept to production.

• Create multi-step reasoning agents, workflows for tool/function-calling, and multi-agent architectures using LangGraph, AutoGen, CrewAI, or tailored orchestration.

• Design and implement scalable RAG pipelines, encompassing chunking, embeddings, vector search, and hybrid retrieval.

• Assess and choose foundation models based on their performance, accuracy, latency, cost, and business needs.

• Formulate strategies for prompt engineering, model routing, fine-tuning, and optimization.

• Take ownership of technical architecture choices for scalable, dependable, and cost-effective LLM applications.

• Set engineering standards for testing, evaluation, observability, guardrails, mitigation of hallucination, and production monitoring.

• Create APIs, microservices, and cloud-native architectures that support AI applications at scale.

• Propel AI/LLMOps practices throughout the model lifecycle management, deployment, monitoring, and continuous enhancement.

• Lead, mentor, and nurture AI/ML and backend engineers.

• Conduct reviews of technical designs, architecture discussions, and code reviews.

• Establish engineering best practices and endorse high standards for AI development in production.

• Provide technical guidance while being actively engaged in intricate engineering challenges.

• Collaborate with Product, Data Science, Platform, Security, and Compliance teams to deliver AI solutions that align with business goals.

• Ensure AI systems comply with privacy, security, compliance, and responsible AI standards.

• Clearly articulate complex technical concepts to senior leadership and business stakeholders.

• Represent the AI engineering division in strategic conversations regarding GenAI technology and roadmap strategies.

⛳️ Requirements

• Over 10 years of comprehensive software engineering experience, including a minimum of 4 years working directly with AI/ML systems.

• At least 2 years of hands-on experience in building and deploying LLM-based or agentic AI applications in a production setting.

• Profound expertise in LLM application development, RAG, embeddings, vector databases, prompt engineering, and AI agents.

• Practical experience with multi-agent systems, tool/function calling, memory management, planning, and reasoning workflows.

• Strong foundation in Python and software engineering principles, with experience in building scalable, distributed, production-grade systems.

• Familiarity with APIs, microservices, cloud-native architecture, and at least one major cloud platform such as AWS, Azure, or GCP.

• Hands-on experience with MLOps/LLMOps tools like MLflow, LangSmith, Weights & Biases, or similar platforms.

• Working knowledge of LLM fine-tuning and evaluation methods, including LoRA/PEFT, RLHF concepts, and offline/online evaluation frameworks.

• Demonstrated ability to provide technical leadership, mentor engineers, make architectural decisions, and collaborate across teams.

• Excellent communication skills, capable of translating complex technical concepts into clear discussions for business and executive audiences.

• Experience in deploying and fine-tuning open-source models such as Llama or Mistral, in addition to proprietary models/APIs.

• Contributions to AI/GenAI open-source projects, technical publications, or conference presentations.

• Experience in building AI solutions within regulated sectors such as finance, healthcare, or telecommunications.

• Knowledge of AI guardrails, red-teaming, responsible AI practices, and model safety/evaluation frameworks.

• Previous formal experience in people management.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional development and continuous learning.

• Supportive and collaborative team environment.