AI Developer

Talentfoot Executive Search; Chevy Chase (MD); On-site; USD 145,000 - 200,000; Full time

Job summary

Talentfoot Executive Search is partnering with a nonprofit research and philanthropic institution to stand up a brand-new AI function. You will own the full lifecycle from model selection to deployment and operations, with direct visibility to senior leadership and across administrative and operational functions.

The role carries immediate impact as systems move from idea to production, with a growth trajectory as the team scales and patterns are defined for the function’s expansion.

Qualifications

• 6+ years in software engineering with 3+ years shipping ML/DL systems; 2+ years beyond generative AI.
• Strong proficiency in Java and/or Python.
• Experience with CI/CD, infrastructure as code, and multi-cloud (AWS/Azure/GCP).

Responsibilities

• Design and build production AI systems within a delivery team to ship collaboratively.
• Choose the right ML approach for each problem and defend it with reasoning.
• Build within reference architectures and share improvements with the team.
• Design evaluation methodology covering precision, recall, calibration, drift, metrics, and A/B testing.
• Own deployment and operations end to end, including CI/CD and observability.
• Handoff to receiving teams with runbooks, docs, and on-call readiness.
• Translate trade-offs to business stakeholders and communicate with engineers.

Skills

Java

Python

Production ML systems

Deep learning

Model evaluation

CI/CD

Infrastructure as code

Cloud platforms (AWS/Azure/GCP)

LangGraph/Strands familiarity

Frontend experience (React)

Tools

Terraform

Kubernetes

Docker

Vector databases

Retrieval systems

Knowledge graphs

Job description

Company Overview

A nonprofit research and philanthropic institution recognized for its long-standing commitment to scientific discovery is investing in a newly formed function dedicated to embedding AI into how the organization operates day to day. This team sits close to the executive suite, reporting through senior leadership, which reflects the strategic weight placed on this work. The culture favors integration over isolation. Developers here are woven into delivery teams alongside engineers, architects, and business partners, rather than siloed off to work on narrow pieces of a larger puzzle. As this function scales, it is building out the team that will define how AI moves from idea to production across the organization.

Position Overview

This is a rare opportunity to help stand up a brand new AI function from the ground up, with direct visibility to executive leadership and a mandate to change how a respected research institution operates. First, the scope is genuinely full lifecycle: model selection, evaluation design, deployment, and operations all fall under one seat, not split across teams. Second, the impact is immediate and visible, since the systems built here will be adopted across administrative and operational functions organization-wide. Third, the growth trajectory is real. The team is expanding beyond this initial hiring round, and early members will shape the patterns, architecture, and culture the function scales on.

Position Responsibilities

• Design and build production AI systems embedded within a delivery team, working alongside engineers, architects, and business partners to ship collaboratively rather than in isolation.
• Select the right technical approach for each problem, whether that means a large language model with retrieval, a gradient boosted tree, or a well featured regression model, and be able to defend that choice with sound reasoning.
• Build within established reference architectures and shared engineering patterns, contributing improvements back to the team when gaps are identified.
• Design evaluation methodology before any system reaches production, covering precision, recall, calibration, drift, business outcome metrics, and A/B testing where appropriate.
• Own deployment and operations end to end, including CI/CD, infrastructure as code, observability, and cost, with production considerations built in from the first commit.
• Partner with receiving teams on handoff, including documentation, runbooks, on call posture, and ownership transition, so systems remain operable by others.
• Translate technical trade-offs for business stakeholders while also communicating at a peer level with engineering teams, moving fluidly between both audiences.

Position Qualifications

• A demonstrated track record of shipping production enterprise systems, with clear ownership of outcomes from design through operation.
• 6 or more years of hands‑on software engineering experience, including at least 3 years building and shipping production machine learning or deep learning systems, with at least 2 years of that experience beyond generative AI specifically.
• Strong proficiency in Java and/or Python.
• Hands‑on experience with classical machine learning techniques (gradient boosting, regression, clustering, tree based methods, dimensionality reduction) as well as deep learning.
• Experience designing evaluation frameworks for production ML systems, including offline and online evaluation, A/B testing, and statistical inference.
• Fluency with infrastructure as code (Terraform or comparable), container orchestration, and CI/CD, with the ability to work across AWS, Azure, and GCP without dependence on a single provider.
• Familiarity with agentic AI frameworks such as LangGraph or Strands.

Preferred

• Experience with front end frameworks such as React, for building end to end user facing AI features.
• Production experience with vector databases, retrieval systems, or knowledge graphs.
• Familiarity with MLOps tooling, including model registries, feature stores, or training pipeline orchestration.
• Prior experience in research, academic, or mission driven institutional environments.
• Background as a forward deployed engineer or solutions engineer, comfortable being client facing while owning technical delivery.

Compensation Range: $145,000 - $200,000 plus a competitive benefits package.