Jobs Companies Ensono Associate Machine Learning AI Engineer

About this Associate Machine Learning AI Engineer role at Ensono

Ensono · Remote · Remote - United States

At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things!  We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation.

 

We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. These five traits are the key to achieving our purpose - Honesty - Reliability - Curiosity - Collaboration - Passion

 

About the role and what you'll be doing: The Junior AI Engineer is the first dedicated engineering hire supporting a new Finance AI Transformation. This function is chartered with a mandate to identify high-impact workflows across Finance and corporate functions, and release AI-enabled solutions that deliver measurable outcomes — from accelerating commercial cycles to improving the quality and speed of decision-making.

This is an applied engineering role. The Junior AI Engineer works alongside the VP, Finance AI Transformation to build production tools that replace manual workflows across Finance, Sales Operations, Procurement, and other corporate functions. Every tool is headless, API-first, and agent-callable by default — engineered so a human can use it directly and an AI agent can invoke it as part of a larger workflow. The work happens in an AI-paired development environment, not a chat interface. Paired development between the engineer and AI tooling is the standard mode of work — successful candidates have already internalized this pattern.

 

This role is internal-facing and offers meaningful exposure to senior leaders across the Office of the CFO and adjacent corporate functions. The tools you release feed directly into deliverables reviewed at the CFO level and become part of a compounding catalog of AI-native solutions across Ensono corporate functions.

 

What You Will Do: 

  • 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.

 

We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. If you do not meet all of the Preferred Qualifications, we still encourage you to apply. 

 

Required Qualifications

  • 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.

 

Preferred Qualifications

  • Hands-on experience with the Anthropic Claude API, including streaming, tool use, prompt caching, or extended thinking.
  • Familiarity with the Model Context Protocol (MCP), agentic tool design, or multi-step agent workflows.
  • Familiarity with multiple AI coding agents and harnesses — comfort moving fluidly between tools rather than being locked into a single environment. Examples include Claude Code (Anthropic), Codex (OpenAI), OpenClaw, Hermes (Nous Research), Goose (Block), Aider, Cline, OpenHands, or opencode.
  • Familiarity with running and evaluating open-weights or open-source language models locally — examples include Phi (Microsoft, MIT-licensed), Gemma 4 (Google, Apache 2.0), Llama (Meta), Mistral (Apache 2.0), Qwen, or DeepSeek — using runtimes such as Ollama, llama.cpp, or vLLM. Awareness of when a local model is the right answer over a frontier API call.
  • Experience building data pipelines, ETL, document processing, OCR, or NLP-based extraction systems.
  • Exposure to integrating with enterprise systems — ERP (NetSuite, SAP), CRM (Salesforce), or finance / procurement platforms.
  • Open-source contributions, published research, or portfolio work in applied ML, NLP, or agentic AI.
  • Familiarity with FinOps practices, cost-aware engineering, or per-use-case spend tracking.
  • Experience designing software for both human and agent consumption — API-first design, structured outputs, machine-readable contracts.
  • Familiarity with API key and secrets management practices (Bitwarden Secrets Manager, GitHub secrets, environment variable hygiene).
  • Experience with cloud infrastructure (AWS, Azure, or GCP), containerization (Docker), or platform-level deployment patterns.
  • Front-end experience with React (or a comparable framework) for building tool UIs and lightweight internal apps.

 

Why Ensono?

Ensono is a place to make better happen – for our clients and for your career. You can do great things through innovation or collaboration, by learning or volunteering, or to promote diversity and inclusion. You can do great things for your own health or for a healthier planet. Whatever it means to you to do great things we want Ensono to be the place you can do it. 

 

We are a client-facing business, but we do encourage clients to allow us to work remotely most of the time so if you are not required to be on a client site, you can choose to work from home or in our Ensono offices.

 

Some of our benefits include:

  • 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

 

As of the date of this posting, a good faith estimate of the current pay scale for this role is $100,000 to $138,000 annually based on a full-time schedule. Please note that placement in the range may vary based on numerous factors including but not limited to skills, experience, internal equity, and business needs. In addition to base salary, other compensation programs include an annual bonus plan based on company and individual performance and an equity grant under our Associate Equity Appreciation Program.

 

Ensono is an Equal Opportunity/Affirmative Action employer. We are committed to providing equal employment to our Associates and building a diverse and inclusive workforce. All qualified applicants will be considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or other legally protected basis, in accordance with applicable law.

 

Pay transparency nondiscrimination statement/posting OFCCP’s pay transparency policy can be found on OFCCP’s website.

 

If you need accommodation at any point during the application or interview process, please let your recruiter know or email USTalentAcquisition@ensono.com.

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How this AI Engineer salary compares

This role pays $119,000/yrbelow the typical range for AI Engineer roles.

$120,820 median $200,000 $287,282

Typical range $165,000–$243,000/yr, from 1,970 comparable AI Engineer listings on JobsRadar (pay annualized to USD). See AI Engineer salary insights →

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