We are seeking a highly skilled and motivated Senior Lead AI Engineer responsible for designing, developing, and delivering high-quality software solutions. This role emphasizes deep technical proficiency, innovation, and hands-on development, including advanced work in AI technologies such as prompt engineering and large language models (LLMs).
This role combines hands-on technical expertise with leadership responsibilities, making it ideal for someone who thrives in a fast-paced environment and is passionate about building scalable, high-quality systems. You will play a key role in shaping technical direction, mentoring team members, and ensuring successful delivery of projects aligned with business goals.
Key Responsibilities
- Design and develop LLM orchestration and prompt engineering for complex, long‑running workflows.
- Design human‑in‑the‑loop mechanisms and ensure transparency and explainability of AI‑driven decisions.
- Develop robust evaluation frameworks, guardrails, and reliability engineering practices for LLM‑powered systems.
- Develop multi‑agent systems, including agent roles, coordination, memory management, and goal alignment.
- Integrate, optimize, and evaluate LLMs across agentic AI, retrieval‑augmented generation (RAG), and prompt management platforms.
- Build data pipelines and automation for ingesting, transforming, and monitoring diverse content sources.
- Collaborate closely with AI Product Management, UIUX Designer, Architecture, Data Acquisition, and Data Lakehouse Engineering teams.
- Own project delivery timelines, manage risks and dependencies, and ensure successful on‑time execution.
- Stay up to date with emerging AI/ML frameworks, techniques, and tooling.
Qualifications
- Bachelor’s or master’s degree in computer science, Engineering, or a related technical field.
- Proven software engineering experience with a strong record of leading and delivering successful projects.
- Deep understanding of software architecture, microservices, API design, and event‑driven patterns.
- Proficiency in modern programming language, such as Java or Python.
- Hands‑on experience with AI / LLM technologies, including prompt engineering, evaluation, fine‑tuning, embeddings, RAG, and model deployment.
- Experience with cloud platforms (AWS) and containerization technologies such as Docker and Kubernetes.
- Familiarity with modern observability practices, including metrics, distributed tracing, and log aggregation, CI/CD pipelines, and DevOps practices.
- Excellent problem‑solving, communication, and leadership skills.
- Ability to operate independently while enabling team success
- Nice to Have : Experience building AI infrastructure—evaluation pipelines, prompt/version management, vector or embedding stores, and model serving—with the ability to optimize and fine‑tune models for latency, quality, and cost.