The AI Engineer will be part of Tech Consulting firm s Forward Deployed Engineering team supporting the Client s AI-Assisted SDLC Pilot Program . Working closely with the onsite AI Architect , this role is embedded directly alongside the Bank development squads configuring AI tooling, operating governance controls, and enabling developers through daily paired coding sessions. The AI Engineer reports to the TECH CONSULTING COMPANY Engagement Lead and plays a critical role in ensuring the pilot produces measurable, evidence-based productivity outcomes.
Responsibilities == RECRUITERS MUST RUN CHECKLIST KEYWORDS UNDERLINED
Participate in codebase assessments to evaluate the Bank s existing technology stack, development workflows, and AI readiness <--- multi programming languages, would be good to have, python and Java to be able to look at code base Configure and maintain squad development environments, including AI coding tools, context files, and agent configurations within the Bank s infrastructure Set up and operate governance tooling including PromptBOM logging, SAST rulesets for AI-generated code, and secrets scanning pipelines python Embed daily within Bank engineering squads during pilot execution reviewing AI-flagged pull requests, pair-programming, and coaching developers on AI-assisted workflows Build and refine custom agents, prompt libraries, and steering files based on pilot learnings and squad feedback Document ways of working, training materials, and the AI-SDLC playbook content in collaboration with the AI Architect Transition from embedded driver to coaching role during the Optimization & Expansion phase, guiding new squads through onboarding Harden the agent library and toolchain configurations for production-readiness during capability transfer Support the train-the-trainer program by teaching Bank engineers to independently configure, maintain, and extend the AI tooling
Candidate Requirements RECRUITERS MUST RUN CHECKLIST KEYWORDS UNDERLINED 5+ years of software engineering experience across all technologies and back-end technologies
Hands-on experience with AI coding assistants (e.g., GitHub Copilot, Claude Code, Cursor, Amazon Q Developer ) in day-to-day development workflows Strong proficiency in modern web frameworks, RESTful APIs, and at least one major cloud platform (AWS, Azure, or Google Cloud Platform) Solid understanding of CI/CD pipelines, Git workflows, pull request reviews, and automated testing practices Experience with static analysis tools (SAST), code quality gates, and security scanning i n enterprise development environments Ability to write clear technical documentation, training materials, and process guides Bachelor s degree in Computer Science, Software Engineering, or a related field
Additional Skills
Experience with prompt engineering or building custom AI agents/skills is a plus Familiarity with developer productivity measurement frameworks ( e.g., SPACE, DORA metrics) is a plus Prior experience working on client-embedded or forward-deployed engineering engagements is highly desirable Knowledge of compliance and governance requirements in regulated industries (financial services, government) is a plus Experience mentoring or training junior developers or conducting technical workshops is a plus
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