Associate Machine Learning, AI Engineer

Ensono

Junior AI Engineer at Ensono supporting finance AI transformation. Building AI-enabled tools to improve workflows across corporate functions.

Posted 7/15/2026full-timeRemote • 🇺🇸 United StatesJuniorMid-Level💰 $100,000 - $138,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong proficiency in Python and API design, with a focus on security-conscious engineering practices and cost-aware coding. Engages effectively with business stakeholders to translate technical requirements into actionable solutions while utilizing AI-paired development environments.

Highest-signal resume keywords

Python FluencyAPI DesignAI-Paired Development EnvironmentSecurity-Conscious EngineeringToken-Cost Awareness

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptJavaScriptGoJavaC#API IntegrationData ManipulationProduction-Quality ScriptsVersion Control

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationStakeholder EngagementClarifying QuestionsBias Toward Adoption

Tools & Technologies

Claude CodeCursorGitHub CopilotGitCI/CD ConceptsBitwarden

Industry Keywords

Token EconomicsPrompt CachingModel SelectionData Exposure RisksAI Spend Finance Policy

Tech Stack

Tools & technologies

GoJavaJavaScriptPythonTypeScript

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Comp & perks

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