Senior AI Engineer
About The Position
We are seeking a hands-on Senior AI Engineer with a strong foundation in traditional Machine Learning and practical, real-world experience building and deploying LLM- and GenAI-driven systems. This role focuses on designing, engineering, and hardening production-grade AI solutions that are embedded into business workflows—not research prototypes. You will work in small, high-impact delivery teams (2–3 engineers per initiative) and spend the majority of your time (~70–75%) building systems end to end, while also contributing to solution design, technical decision-making, and cross-functional collaboration.
Requirements
- 10-12 years of overall software engineering experience, including prior work as an ML Engineer or equivalent.
- Strong backend development skills (Python, Java, Node.js, or similar languages).
- Experience designing and building REST or gRPC-based services.
- Solid understanding of distributed system design.
- Containerization and orchestration experience (Docker, Kubernetes).
- Hands-on experience across traditional ML and modern GenAI systems.
- Proficiency with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or equivalents.
- Experience building or deploying ML-driven production systems.
- Experience building or deploying LLM-based applications.
- Ability to select ML vs. LLM-driven approaches based on business and operational constraints.
- Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP).
- Experience with CI/CD pipelines and deployment automation.
- Understanding of model, code, and configuration versioning best practices.
- Experience implementing logging, monitoring, and tracing for production systems.
- Familiarity with system resilience patterns such as rate limiting, failover strategies, and kill-switch mechanisms.
- Strong ability to solve ambiguous, real-world engineering problems.
- Comfortable working in fast-moving, iterative environments.
- Ownership mindset with a bias toward practical, scalable solutions.
- Experience working in cross-functional teams.
- Ability to clearly articulate technical and business trade-offs, including LLM vs traditional ML, build vs buy decisions, and speed vs robustness.
Nice To Haves
- Experience with enterprise AI platforms or internal AI frameworks.
- Prior production experience with agentic architectures.
- Prior production experience with multi-agent systems.
- Prior production experience with RAG-based systems at scale.
- Exposure to AI governance, safety, and compliance considerations.
- Experience mentoring junior engineers or owning technical modules.
- Hands-on experience optimizing performance and cost for AI workloads.
Responsibilities
- Designing, engineering, and hardening production-grade AI solutions.
- Building systems end to end.
- Contributing to solution design.
- Contributing to technical decision-making.
- Cross-functional collaboration.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
