Associate Machine Learning AI Engineer

About this role

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 pa

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