Applied AI Engineer - Agentic Workflows (Singapore)

About Cohere

Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Why this role?

We’re a fast-growing startup building production-grade AI agents for enterprise customers at scale. We’re looking for Applied AI Engineers who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs)—from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows.

In this role, you’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.

You’ll collaborate closely with customers, product, and platform teams, and help shape how agentic systems are built, evaluated, and deployed at scale.

What You’ll Do

• Work with enterprise customers and internal teams to turn business workflows into scalable, production-ready agentic AI systems.
• Design and build LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability.
• Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions.
• Define and apply evaluation and quality standards to measure success, failures, and regressions.
• Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails.
• Contribute to shared frameworks and patterns that enable consistent delivery across customers.

Required Skills & Experience

• Bachelor’s degree in Computer Science or a related technical field.
• Strong programming skills in Python and/or JavaScript/TypeScript.
• 3+ years of experience building and shipping production software; 2+ years working with LLMs or AI APIs.
• Hands-on experience with modern LLMs (e.g., GPT, Claude, Gemini), vector databases, and agent/orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, or custom solutions).
• Practical experience with RAG, agent workflows, evaluation, and performance optimization.
• Strong agent design skills, including prompt engineering, tool use, multi-step agent workflows (e.g. ReAct), and failure handling.
• Ability to reason about and balance trade-offs between customization and reuse, as well as autonomy, control, cost, latency, and risk.
• Strong communication skills and experience leading technical discussions with customers or partners.

Nice-to-Have

• Experience working in a fast-moving startup environment.
• Prior work delivering AI or automation solutions to enterprise customers.
• Familiarity with human-in-the-loop workflows, fine-tuning, or LLM evaluation techniques.
• Experience with cloud deployment and production operations for AI systems.
• Background in applied ML, NLP, or decision systems.

Additional Requirements

• Strong written and verbal communication skills.
• Ability and interest to travel up to 25%, flexible.

Why Join Us

• Build production-grade AI agents used in real enterprise workflows.
• Operate at scale while retaining end-to-end ownership.
• Work on hard problems in agent design, evaluation, and reliability.
• Shape shared platforms and standards, not just individual features.
• Move fast with a high bar for quality, safety, and reliability.

If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!

We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

Full-Time Employees At Cohere Enjoy These Perks

• 🤝 An open and inclusive culture and work environment
• 🧑‍💻 Work closely with a team on the cutting edge of AI research
• 🍽 Weekly lunch stipend, in-office lunches & snacks
• 🦷 Full health and dental benefits, including a separate budget to take care of your mental health
• 🐣 100% Parental Leave top-up for up to 6 months
• 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
• 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
• ✈️ 6 weeks of vacation (30 working days!)

Key skills/competency

The Applied AI Engineer - Agentic Workflows role at Cohere requires a blend of strong software engineering principles and deep expertise in artificial intelligence, particularly in the domain of Large Language Models (LLMs) and agentic systems. Key skills include proficiency in Python or JavaScript/TypeScript, hands-on experience with modern LLMs (like GPT, Claude, Gemini), vector databases, and agent orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex). Candidates must demonstrate practical experience with Retrieval-Augmented Generation (RAG), designing and implementing multi-step agent workflows (e.g., ReAct), prompt engineering, tool use, and failure handling. A solid understanding of agent evaluation, performance optimization, and the ability to balance trade-offs in system design (customization vs. reuse, autonomy vs. control, cost, latency, risk) are crucial. Strong communication skills for customer-facing technical discussions are also essential. Experience in a fast-paced startup environment and prior work with enterprise AI solutions are highly desirable.