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Ensono logo
Ensono

Ensono delivers complete Hybrid IT solutions, from mainframe to cloud, tailored to each client’s journey.

Associate Machine Learning, AI Engineer

AI EngineerMachine Learning EngineerFull TimeRemoteMid LevelTeam 1,001-5,000H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

8 days ago

Salary

$100K - $138K / year

Seniority

Mid Level

Bachelor DegreeEnglishJavaJavaScriptPythonTypeScriptGo

Job Description

Associate Machine Learning, AI Engineer

Ensono

• Release the function's pipeline of production tools — prioritized by business impact as the discovery pipeline surfaces them. • Engage directly with business stakeholders alongside the Solutions Lead — sit in on discovery conversations, ask the technical questions that surface real constraints, and translate what you hear into the right solution form. The Solutions Lead opens the door; the engineer brings the technical eye that decides what actually gets built. • Build headless, API-first, and agent-callable by default — every tool is engineered so a human can invoke it directly and an AI agent can invoke it programmatically as part of a larger workflow. API-first design, structured I/O, clean tool contracts. • Pair-program with an AI-paired development environment (Claude Code, Cursor, Copilot, or equivalent) — treat AI-paired development as the baseline mode of work, not an enhancement. Sustained throughput is the load-bearing promise of this role. • Contribute to a pattern catalog that compounds — document reusable patterns, tool contracts, and architectural decisions so each solution makes the next one cheaper to build. • Build internal tooling for the function’s own operations — including, over time, a FinOps agent that monitors AI usage across the function and surfaces cost-optimization opportunities. • Engineer with token-economics in mind — model routing (Haiku for retrieval and classification, Sonnet for reasoning), prompt caching, output validation, retry/cost discipline. Cost-aware code is good code. • Partner with Internal IT on the graduation pipeline — work alongside IT to harden tools that prove themselves and ensure handoff readiness when a tool graduates to production-grade managed infrastructure. • Practice security-conscious AI engineering — secrets in Bitwarden, environment hygiene, awareness of data exposure risks, and adherence to internal security and AI Spend Finance policy controls. • Document workflows, decisions, and reusable patterns so the work compounds across the Finance AI Transformation function rather than living in one person's head.

Job Requirements

  • Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent demonstrated experience. Recent graduates encouraged.
  • Demonstrated experience using Claude Code, Cursor, GitHub Copilot Workspace, or an equivalent AI-paired development environment to build, release, or meaningfully contribute to a working application — not just casual chat-style use of AI tools.
  • Strong Python fluency, including data manipulation, API integration, and writing production-quality scripts.
  • Comfort with at least one additional language: TypeScript / JavaScript, Go, Java, or C#.
  • Working knowledge of API design (REST, JSON I/O, structured output), version control (Git / GitHub), and basic CI/CD concepts.
  • Token-cost awareness when using LLM APIs — understanding of prompt caching, model selection (Haiku vs. Sonnet vs. Opus), and basic optimization techniques.
  • Security-conscious engineering practice — proper handling of API keys and secrets, awareness of data exposure risks, and adherence to internal security practices.
  • Strong written and verbal communication, with the ability to engage directly with non-technical business stakeholders, listen for real constraints, ask clarifying questions, and translate what you hear into clean technical requirements — and into documentation another engineer (or an AI agent) can pick up later. While the function has a dedicated Solutions Lead for discovery, the engineer is expected to participate in stakeholder conversations, not just receive specs.
  • Bias toward releasing and driving adoption over experimenting — a track record of finishing things, including in side projects, school projects, or internship work.

Benefits

  • Unlimited Paid Days Off
  • Three health plan options through Blue Cross Blue Shield
  • 401k with company match
  • Eligibility for dental, vision, short and long-term disability, life and AD&D coverage, and flexible spending accounts
  • Paid Maternity Leave, Paternity Leave, and Sabbatical Leave
  • Education Reimbursement, Student Loan Assistance or 529 College Funding
  • Enhanced fertility coverage
  • Wellness program
  • Flexible work schedule
  • Depending on location, ability to take advantage of fitness centers

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