Senior Technical Lead – Generative AI

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

📋 Description

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

• Create multi-step reasoning agents, tool/function-calling workflows, and multi-agent architectures utilizing LangGraph, AutoGen, CrewAI, or custom orchestration methods.

• Develop and productionize scalable Retrieval-Augmented Generation (RAG) pipelines, which encompass chunking, embeddings, vector search, and hybrid retrieval techniques.

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

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

• Take ownership of technical architecture decisions to ensure LLM applications are scalable, reliable, and cost-effective.

• Set engineering standards that encompass testing, evaluation, observability, guardrails, hallucination mitigation, and production monitoring.

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

• Advance AI/LLMOps practices throughout model lifecycle management, deployment, monitoring, and ongoing improvement.

• Guide, mentor, and nurture AI/ML and backend engineering teams.

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

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

• Offer technical guidance while remaining 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 that AI systems adhere to privacy, security, compliance, and responsible AI standards.

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

• Act as a representative for the AI engineering function in strategic discussions regarding GenAI technology and roadmap decisions.

⛳️ Requirements

• Over 10 years of software engineering experience, including more than 4 years directly working with AI/ML systems.

• A minimum of 2 years of hands-on experience in building and deploying LLM-based or agentic AI applications in production environments.

• In-depth 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 developing scalable, distributed, production-grade systems.

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

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

• Knowledge of LLM fine-tuning and evaluation techniques, including LoRA/PEFT, RLHF concepts, and both offline and online evaluation frameworks.

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

• Excellent communication skills with the capability to distill 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, as well as proprietary models/APIs.

• Involvement in AI/GenAI open-source projects, technical publications, or conference presentations.

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

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

• Prior formal experience in people management.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance plans.

• Generous paid time off and holiday leave.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• Collaborative and innovative work environment.