Forward-Deployed AI Engineer
Listed on 2026-10-09
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Software Development
AI Engineer (Applied/Software)
Forward-Deployed AI Engineer
Location:
Remote with ~40% travel
Employment Type:
Direct/Full-time Industry: Private Equity Compensation: 150k-250k + bonus
Schedule:
day About the Opportunity:
The Forward-Deployed AI Engineer will be forward deployed to drive measurable business impact across portfolio companies through AI-powered automation. Our client is building a small, high-impact AI team to accelerate value creation across our portfolio companies. This role sits within Portfolio Operations, reports to the Operating Partner, AI, and works alongside the Strategy and Transformation Operating Partners, who identify high-value opportunities and direct focus areas.
WhyYou'll Love Working Here:
- Supportive, team-driven culture that values collaboration, transparency, and accountability
- Opportunity to grow your career with a global workforce solutions leader serving multiple industries
- People-first environment that encourages employees to bring their authentic selves to work
- Strong focus on partnership, innovation, and delivering meaningful results for clients and candidates
This role offers the chance to join a company that prioritizes both people and performance-where your contributions directly impact client success while giving you room to grow and develop professionally.
About Acara SolutionsAcara is a premier recruiting and workforce solutions provider-we help companies compete for talent. With a legacy of experience in various industries worldwide, we partner with clients, listen to their needs, and customize visionary talent solutions that drive desired business outcomes. We leverage decades of experience to deliver contingent staffing, direct placement, executive search, and workforce services worldwide.
Sound like a good fit?What You'll Do:
As a Forward-Deployed AI Engineer, you will work directly with portfolio companies to identify, evaluate, implement, and measure AI solutions that generate tangible EBITDA impact. The majority of your work will involve selecting and deploying third-party AI platforms, integrating them with existing systems, measuring their impact, and training teams to use them effectively. You will also build custom solutions when off-the-shelf tools are insufficient - and your ability to build is what makes you great at everything else: evaluating vendor claims critically, troubleshooting integrations, training non-technical teams, and knowing when a simple custom solution beats an expensive SaaS contract.
This ranges from lightweight automations built with no-code and low-code platforms (e.g. Claude Cowork, n8n, or Zapier), which are often the fastest and most practical solutions, to fully custom agentic workflows built in Lang Graph or equivalent frameworks when the use case demands it. Knowing which approach fits the problem is as important as being able to execute either one.
Evaluation, Integration & Vendor Management:
- Evaluate and select third-party AI platforms and vertical SaaS tools using a structured build-vs.
-buy framework; assess vendor architecture, identify failure modes, and make go/no-go recommendations backed by data rather than demos. - Lead end-to-end implementation: configure workflows, integrate with existing enterprise systems (ERP, CRM, HRIS, data warehouses) via APIs, webhooks, and MCP connections, validate data integrity, and manage go-live.
- Run structured proofs of concept with upfront success criteria, instrumented measurement, and edge-case testing before committing to full rollout.
- Manage vendor relationships and hold partners accountable to delivery timelines and performance targets.
- Define baselines and success metrics before every deployment; build evaluation frameworks to monitor output quality, catch silent degradation, and track user adoption over time.
- Translate operational results into EBITDA impact and provide data-backed progress updates to Operating Partners and portfolio company leadership.
- Deliver measurable results within compressed private equity timescales, typically targeting quick wins within 30 to 60 days alongside longer-horizon transformation projects.
- Design and build targeted AI automation solutions using Python, Claude Code, Codex, Gemini, and other leading platforms (e.g. agentic workflows, document processing pipelines, RAG knowledge systems, and intelligent assistants), scoped to fill gaps that vendor products cannot address.
- Comfortable building…
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