AI & ML Engineer

Asteri is an AI-native Work Intelligence and Orchestration Platform that gives large enterprises the intelligence to understand how work is performed today and how it should be performed in the era of AI, eliminating inefficiencies and identifying high-impact opportunities for AI augmentation. Our platform orchestrates AI and human work with enterprise-grade governance, auditability, and measurement built for production environments at scale.

We are looking for an AI & ML Engineer with strong software engineering foundations to join our growing engineering team. This role sits at the intersection of applied AI and production software and focuses on building reliable, scalable, enterprise-ready AI systems.

You will work closely with software engineers and platform teams to design, deploy, and operate AI-powered capabilities that directly power our core product. This is not a research-only role: success is measured by production impact, reliability, and customer value.

If you are excited about building AI systems that operate in real enterprise environments with real constraints, real users, and real accountability - we’d love to talk.

Design, build, and operate production-grade AI/ML systems that power Asteri’s orchestration platform

Collaborate closely with backend, platform, and frontend engineers to integrate AI capabilities into scalable, reliable product workflows

Deploy and iterate on LLM-based applications in production, continuously evaluating quality, latency, and cost

Own retrieval and agentic systems (e.g., RAG pipelines, workflow agents, policy-driven logic) end-to-end

Define and run rigorous evaluation and testing for AI systems, including offline experiments and production monitoring

Improve model performance and system behavior over time through experimentation, tuning, and system-level optimizations

Implement strong engineering practices for AI development, including testing, CI/CD, versioning, and rollback strategies

Stay current with advances in applied AI and generative models and translate relevant techniques into practical product improvements

Partner with cross-functional teams to understand product requirements and translate them into robust AI solutions

Experience building applications with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face

Deep experience with retrieval-augmented generation (RAG) systems and optimization techniques

Familiarity with ML lifecycle and experimentation tools (e.g., MLflow, Weights & Biases, DVC)

Experience building distributed or data-intensive systems

Exposure to enterprise or regulated environments

You’ll have direct ownership of critical AI systems, real production impact, and the opportunity to shape how AI is safely and effectively deployed alongside humans at scale. Competitive compensation with remote-friendly culture, and a pragmatic, production-first approach to AI.