Product Engineer with strong product sense and engineering skills for a leading IT services company. Taking ambiguous goals and delivering software solutions with minimal guidance.
About the role
- Senior AI Engineer developing AI/ML solutions for fabric's AI Commerce Operating System. Leading technical design, system implementation, and collaboration with cross-functional teams.
Responsibilities
- Own the full lifecycle of AI/ML solutions—from problem framing and system design through training, evaluation, deployment, and iteration in production.
- Translate ambiguous business problems into scalable AI architectures and agent behaviors.
- Drive technical decisions around model selection, data strategy, and evaluation frameworks.
- Design and implement production-grade agentic systems, including reasoning, planning, orchestration, memory, and tool-use.
- Ensure systems are reliable, observable, and perform at scale.
- Improve system reliability through metrics, alerts, drift detection, and performance monitoring.
- Evaluate and integrate emerging techniques (e.g., LLMs, RAG, knowledge-augmented systems) with a strong focus on production readiness and ROI.
- Help build intelligent data products such as recommendation engines, personalization, categorization, search ranking, forecasting, and fraud detection.
- Collaborate across teams and work closely with product managers, designers, and software engineers to build AI agents that solve real world problems.
Requirements
- 7+ years of experience in applied ML / AI engineering, with a strong track record of shipping and operating production AI systems in high-growth startups.
- Experience in product-focused environments building end to end SaaS products, where ownership and execution matter.
- Demonstrated ability to work in ambiguous, 0→1 problem spaces.
- Proven experience building and deploying ML models for real-world use cases (e.g., recommendations, search, NLP, categorization).
- MLOps & Infrastructure: Deployment, monitoring, CI/CD, ML pipelines, containerization, and cloud infrastructure.
- Full-stack ML expertise across: Data Engineering (feature engineering/ store, distributed data processing).
- Strong programming skills using Spark, Python, TensorFlow/PyTorch, MLFlow, Airflow, Docker, Kubernetes, etc.
- Experience with Knowledge graphs is a big plus.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Econometrics/ Statistics, or related field—or equivalent practical experience.
- Passion for building usable, scalable products — not just research or models.
- Clear communicator with a collaborative mindset, eager to grow and contribute within a small, fast-paced team.
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