Forward Deployed Engineer (ML/AIOps)
Salary: $50,000 – $55,000 per month
About the role
Work with business stakeholders to define problems, priorities and success measures for AI and systems initiatives. Translate requirements into solution design covering options, architecture, build-versus-buy, risks and a practical delivery path. Develop, integrate and test solutions in the operating environment, from prototype through pilot and handover to production support.
Key responsibilities
Work with business stakeholders to define problems, priorities and success measures for AI and systems initiatives
Translate requirements into a solution design covering options, architecture, build-versus-buy, risks and a practical delivery path
Develop, integrate and test solutions in the operating environment, from prototype through pilot and handover to production support
Implement AI-enabled workflows (including agents, retrieval and automation) where they are justified by the use case
Apply AI-assisted development tools to accelerate delivery while maintaining review, security and operational standards
Present designs and trade-offs to non-technical stakeholders and coordinate with IT and vendors on access, constraints and handover
Document reusable patterns and feed implementation lessons into subsequent engagements
About you
Degree in computer science, engineering, information systems, or a related discipline
5+ years of experience working in a solution delivery role
Hands-on software or AI engineering experience, mainly backend but front-end experience is appreciated
Ability to communicate with business stakeholders and to develop working solutions
Python is expected; TypeScript or a similar language is useful
Ability to design solutions under constraints of systems, data, security and time, and to adjust the design based on implementation findings
Familiar with AI frameworks such as LangChain and protocols such as MCP, A2A
Working knowledge of APIs, data stores and at least one cloud platform
Experience with large language models, retrieval-augmented generation or agent patterns is useful
Production implementation experience is an advantage