FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.

Forward Deployed Engineer, AI Engineer
Partners GroupForward Deployed Engineer in AI Pods building production-grade AI solutions for financial markets. Collaborating with business and technology teams to deliver impactful change and governance.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and delivering AI products end-to-end, with a strong focus on integrating AI solutions within the financial industry. Proficient in modern programming languages and data platforms, ensuring secure and compliant solutions while driving measurable business outcomes.
Highest-signal resume keywords
AI Product DevelopmentMachine Learning EngineeringPython ProgrammingAWS Certified Machine Learning Engineer – AssociateFinancial Industry Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningArtificial IntelligenceData ScienceSoftware EngineeringPostgreSQLMS SQLSnowflakeLLM Application DevelopmentSystem IntegrationCode Quality
Soft Skills
CollaborationCommunicationProblem-SolvingTeam-Oriented MindsetSelf-Starter
Tools & Technologies
AWSAPIsVersion Control SystemsDevOps PracticesData Platforms
Certifications & Qualifications
AWS Certified Machine Learning Engineer – Associate
Industry Keywords
Financial MarketsGovernanceRisk ManagementComplianceBusiness Value
Tech Stack
Tools & technologiesAWSPostgresPythonSQL
About the role
Key responsibilities & impact- Partner with business team to identify and prioritize high-impact AI use cases, including buy-vs-build recommendations.
- Design and deliver AI products end-to-end, from problem definition through prototype, pilot, and production handover.
- Build AI-powered solutions.
- Develop robust datasets along with retrieval and reasoning pipelines across different business functionalities.
- Integrate with vendor AI platforms and internal AI solutions, reusing existing capabilities where possible.
- Instrument solutions to track adoption, quality, business value, ROI, cost, and risk.
- Partner with technology team to ensure secure, compliant, auditable, and supportable solutions.
- Run rapid evaluation cycles and contribute reusable components, patterns, and tools for wider adoption.
Requirements
What you’ll need- Bachelor's or Master's degree in Data Science, Computer Science, Artificial Intelligence / Machine Learning, Software Engineering, Quantitative Finance, or a related discipline
- Background in the financial industry with a solid understanding of financial markets, and 5+ years of professional experience in traditional software engineering or a similar role.
- Demonstrated experience (minimum 2 years) building and shipping ML/AI products in production environments, ideally with measurable business outcomes.
- AWS certification preferred, ideally AWS Certified Machine Learning Engineer – Associate
- Strong proficiency in a modern development language such as Python.
- Hands-on experience with modern databases and data platforms such as PostgreSQL, MS SQL, Snowflake, or comparable technologies.
- Strong hands-on engineering ability to deliver LLM applications end-to-end (e.g., Python, APIs, system integration, testing, deployment readiness).
- Hands-on experience designing and developing software solutions in enterprise or team-based environments, with a strong focus on code quality, sound design decisions, and collaboration.
- Familiarity with the software development lifecycle, version control systems, and modern DevOps practices.
- Ability to translate ambiguous business problems into product scopes, roadmaps, and iteration plans with clear success metrics and value gates.
- Comfortable working with sensitive/confidential data and partnering with governance, risk, and security stakeholders to embed controls from the start.
- Strong collaboration and communication skills—able to work embedded within business teams and cross-functionally with other technology teams.
- Driven, self-starter, inclusive, team-oriented mindset
Benefits
Comp & perks- 25 vacation days
- One-month sabbatical after every five years of service
- Lunch stipend
- Fun office and team events, including volunteer opportunities to connect with and help our local communities