Associate Machine Learning, AI Engineer

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🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $100k - $138k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 AI Engineer

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Ensono

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Cloud Services • IT Services • Managed Services

Ensono is a managed service provider and expert technology advisor focused on enabling clients to navigate complex IT environments. Ensono offers services including mainframe-as-a-service, cloud migration, and IT infrastructure management, with a strong emphasis on modernizing legacy systems and optimizing IT operations. The company is recognized for its flexibility and allyship, providing businesses with the ability to adapt and evolve through solutions like Ensono Flex®. It specializes in both mainframe and cloud solutions, holding competency in AWS mainframe modernization and is a global Azure Expert MSP. Ensono acts as an ally, helping companies achieve better business outcomes through IT innovation and strategic technology advisement.

📋 Description

• 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

• 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