Senior AI Product Engineer

Posted on:

November 12, 2025

Job description

The role

As a one person team to start, you are both a product lead and the technical SME. You are ‘on the tools’ bringing your experience building robust, scalable, and maintainable Data and AI business applications as we evolve our technology. You’re also able to lead; able to ‘be Frank’, coaching and mentoring those you manage and those in your squad to improve continuously

In this role, you will work with leaders, who have significant experience and can relate to the challenges that the product and engineering teams face. FrankieOne is a global team and will require coordinating with teams/vendors outside of typical working hours. In this particular role you are expected to primarily work in the office (with some hybrid options) as per the company policy.

Responsibilities

Your ticket to success:

Inspire others. You take great pride in your work, have an eye for detail, and inspire others to do the same. You can manage the design, seek the team’s input, and celebrate your shared success. You coach and mentor junior members of the team, peer-reviewing their work and supporting their development by sharing your knowledge and experience.
Design with quality. You can take a step back from the details, seek to understand the bigger picture and drive appropriate architecture and technology choices. The quality of your work is at the highest level and you’re able to review others' work to ensure it is of the same caliber
Collaborate. You are an active participant in our regular scrum rituals. You communicate well and can work harmoniously alongside both product, other engineers, and QA - identifying areas for automation and supporting testing when required.
Be proactive. Your input and innovation are vital to ensure continuous improvement. You proactively identify areas that need modifying / could be improved across the service and technology stack and drive improvements.
Be an advocate. For FrankieOne, for our product, and our values.

Job requirements

In a previous life, you have:

Recent experience in building AI applications with end to end ownership.
10 plus years experience in engineering teams in an Agile environment using JS based frameworks like React
5 plus years developing & supporting Full Stack TS-based SaaS applications production in AWS/Cloud ecosystem.
Experience in HTML5, ES6, CSS3/Sass, javascript, typescript, React, React Native for Web (optional), npm and other front-end technologies to deliver enterprise grade frontend applications.
Experience in depth of back-end oriented technologies such as nodejs, typescript for managing BFF.

Experience with Data, AI & Architecture

Knowledge and experience in tracking technological developments especially AI with vendor offerings and ability to quickly evaluate their value proposition e.g AWS Bedrock
Experience in architecting & building enterprise grade AI applications with Data and AI governance, AI gateways, context management (RAG), inference/prompt management, tools/functions (MCP, A2A), memory & fine-tuning.
Experience in capturing business requirements from stakeholders to documenting, architect and building AI applications for both internal and external users.
Experience in designing web applications based on AWS well architectured principles, 12 factor web application principles, cloud based software architecture patterns (pub-sub, saga, circuit breaker etc).

Experience with hands on full stack implementation

Experience in designing reactjs based frontend and backend in nodejs or golang.
Experience in designing, mocking, building, and consuming REST, GraphQL, grpc (optional) APIs with JSON payloads.
Experience with AI based integrations using MCP, A2A.
Experience with AI tooling such as AWS Sagemaker, Google Vertex AI.
Experience with relational databases such as Postgres (including managing DB performance via indexing and SQL for query optimization).
Experience with data warehouse such as AWS Redshift
Experience with document databases such as AWS DynamoDB.
Experience with file and block store services such as AWS S3.
Experience with building integration services using SNS, SQS, EventBridge, REST API & GraphQL for microservices and MCP and A2A for AI based integrations.
Experience with containerized services ECS, EKS (optional).

Experience with developer, ops & delivery ecosystem

Experience with quality practices of acceptance criteria on stories, unit testing, system integration testing ,user acceptance testing, business acceptance testing and product validation testing.
Experience developing web applications and services that are production & operationally ready in the AWS cloud environment with feature flags, billing, cloudwatch, alerting, service status dashboard and analytics reporting.
Experience in architecting, designing, building and supporting multiple environments such as Development, QA, UAT, Production.
Experience in using modern tools like Google Workspace, GitHub Copilot, Slack, JIRA, Miro.
Experience in PRD, system and solution design with work breakdown, dependencies with skills and work estimates with effort, duration & costs.
Experience to obtain and maintain ISO27001, SOC2, GDPR in SaaS environments.

Experience with commercial and people leadership

Experience in balancing and managing pre-sales, post-sales and development activities along with prioritization, stakeholder holder management and communications.
Experience in process improvement, change management, data informed & holistic decision making (tech & commercial), critical thinking and problem solving.
3 plus years experience in managing/coaching teams of engineers and/or squads (recruitment, 1:1, coaching, performance reviews and management).
2 plus years experience in commercial management of team/FTE budget planning and execution, vendor/technology selection (RFI, RFP) and contractor/partner management (SOW, project mobilization, performance/status reviews and sign offs)
Excellent written, verbal and presentation at team, squad, guild, department, executive and company level.
Experience working collaboratively in a global & distributed team environment.

Ideally you have:

AWS Certified Machine Learning Specialty
AWS Certified Developer.
AWS Certified Solutions Architect (optional).
Experience with back-end oriented languages such as golang, python (optional).
Passionate about automation, No/Low Code tools (e.g. Tooljet) to build and accelerate delivery.
Exposure to building AI-based models & E2E full stack applications.
Experience working in a fintech startup providing B2B SaaS services.