AI Automations Product Engineer

New

NineTwoThree AI StudioAI, Web, Mobile Applications

Charlotte, North Carolina, United States. Orlando, Florida, United States. Dublin, County Dublin, Ireland. London, England, United Kingdom. Amsterdam, North Holland, NetherlandsFull-TimeMiddle

Salary not disclosed

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Job Details

Required Skills: PythonData engineeringFastAPISlackNotionAWS LambdaPrompt Engineering

Requirements

Ability to surface new approaches, tools, and workflows for knowledge contribution
Experience with continuous R&D of new AI tools, models, and frameworks
Experience in practice building, contributing to project templates, runbooks, and evaluation approaches
Skills in solutions engineering and client delivery
Ability to provide discovery and shaping support, translating business problems into AI solutions
Proficiency in technical feasibility assessment of client data, systems, and APIs
Experience with demo build-out for prospective clients
Capability to provide input for proposals and scope, including architecture and success criteria
Experience with client onboarding and education for delivered systems
Proficiency in project setup and architecture design following engineering and deployment standards
Skills in system and process design, including data flow and AI component integration
Understanding of agentic design and trade-offs, and ability to explain them clearly
Hands-on build experience, writing code using AI development tools
Fluent in Python-first stack, including lightweight web frameworks (FastAPI, Gradio) and serverless runtimes (AWS Lambda)
Expertise in prompt engineering and model selection, balancing accuracy, cost, latency, and privacy
Proficiency in data engineering, including cleaning, structuring, and processing client data
Experience with deployment, working with DevOps teams to deploy services to cloud accounts
Ability to perform validation before production, testing AI outputs against real client data
Experience with project tracking using tools like Monday.com
Skills in client communication, including running technical portions of client meetings
Proficiency in code review and submitting clean PRs
Ability to perform quality assurance, testing AI outputs for failure modes and hallucinations
Experience with handover and documentation, completing delivery checklists

Responsibilities

Surfacing new approaches, tools, and workflows and contributing them to the department's knowledge base and operating models
Spending dedicated hours testing new AI tools, models, and frameworks relevant to client work and sharing findings
Helping shape the department's working methods, contributing to project templates, runbooks, and reusable components
Scoping, shaping, and solutioning new client engagements, then owning the delivery against those briefs
Joining discovery calls and shaping sessions to translate business problems into AI-driven solutions
Evaluating client data, systems, and APIs to determine technical feasibility and flag risks early
Building working demos for prospective clients to demonstrate proposed solutions
Contributing technical detail to proposals and statements of work, including architecture approach and milestones
Helping client teams understand and confidently use delivered systems, including walkthroughs and training
Owning the technical delivery of client projects end-to-end, including project setup and architecture
Designing the end-to-end system, including data flow, AI components, human interaction, and output
Making considered decisions about agentic approaches vs. deterministic pipelines vs. human-in-the-loop steps
Writing code using AI development tools, primarily Python-first stack with lightweight web frameworks and serverless runtimes
Designing and refining prompts, system instructions, and model choices for AI behavior
Cleaning, structuring, and processing client data for the AI layer, building ingestion and processing layers
Working with DevOps to deploy services to client cloud accounts following deployment standards
Testing AI outputs against real client data before go-live and building validation patterns
Tracking projects using Monday.com, following established task, branch, and PR conventions
Joining and running technical portions of weekly client meetings
Submitting clean PRs that pass pre-commit checks and link to tracked work, engaging in constructive code review
Testing AI outputs for failure modes, hallucinations, and edge-case behavior before client exposure
Completing the delivery checklist before project closure, including documented architecture and handover

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