Forward-Deployed AI Engineer
Acara Solutions
Job Title: 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.
Why You'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
Why This Opportunity is Exciting:
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 Solutions
Acara 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 LangGraph 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.
Role Responsibilities:
Third-Party 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.
Measurement and ROI:
- 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.
Custom Development & Deployment:
- 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 lightweight automations using no-code and low-code platforms (Claude Cowork plugins, n8n, Zapier, Make) when simplicity and speed serve the use case better than a custom-coded solution; exercises judgment about when sophistication is warranted and when it is not.
- Develop custom Skills, plugins, and MCP integrations to extend third-party AI platforms within portfolio company environments.
- Implement prompt engineering frameworks, output validation, and governance controls to ensure production-grade reliability across both custom and vendor-deployed systems.
- your build knowledge to strengthen vendor work: evaluate whether a vendor's underlying architecture is sound, identify silent failure modes, and propose improvements that a buyer without technical depth would miss.
Enablement & Adoption:
- Train portfolio company teams on deployed solutions so they can operate, troubleshoot, and extend implementations independently; drive change management to sustain adoption.
- Document every deployment with runbooks, user guides, and playbooks that enable cross-portfolio replication without ongoing support.
Job Requirements
What You'll Bring:
Minimum 3 years experience implementing, integrating and building AI/ML systems
Minimum 3 years experience with AI platforms, RAG architectures, Python, Cloud platforms and 3rd party platform evaluation
What Sets You Apart:
Experience in Private Equity, Management Consulting or Financial Services environments
- Ability to select and appropriate evaluation metrics for a given AI or ML use case; knows how to distinguish signal from noise in model outputs and identify when a strong metric is masking a broken system.
- Ability to design rigorous AI evaluations using golden eval sets, LLM-as-judge, human-in-loop review, and A/B testing with appropriate controls; able to these methods to vendor-deployed systems, not just custom builds.
- Hands-on proficiency with modern AI platforms (Claude Code, Claude Cowork, Codex, Gemini, Cursor, Windsurf, or equivalent) and automation tools (n8n, Zapier, Make, and similar); actively experiments with emerging platforms rather than reading about them passively.
- Solid working knowledge of agentic workflow architecture—orchestrator and sub-agent patterns, state management, tool calling, and failure handling—with hands-on experience in LangChain, LangGraph, or equivalent; able to reason through design choices in a technical conversation, not just configure existing templates.
- Proficiency with RAG architectures, MCP server integration, API architectures, and webhook-based workflow automation; able to connect AI tools to enterprise systems, diagnose integration failures, and ensure data integrity across system boundaries.
- Strong Python skills: able to read, write, extend, and debug production code and AI-generated code; familiarity with cloud platforms (AWS, Azure, or GCP) and standard deployment patterns including containerization and CI/CD.
Working knowledge of common ML model types (clustering, regression, classification, recommendation systems, gradient boosting, deep learning) and evaluation metrics (precision, recall, F1, AUC, RMSE); able to select an appropriate approach for a business
Additional Information:
After you , you may receive a call or message from our AI Talent Scout about this role or other opportunities that match your skills and preferences. AI agent role is to help speed up your hiring process by answering questions, confirming basic information, and identifying whether there's a mutual fit.
The call or chat may be recorded so that our recruiting team can review it - they make all final hiring decisions, while AI agent simply helps move you forward faster. The best part? They are available 24/7, so you can connect whenever it's convenient for you.
By ing for this job, you agree to receive calls, AI-generated calls, text messages, or emails from Acara Solutions and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may . Carriers are not liable for delayed or undelivered messages. You can reply STOP to cancel and HELP for help. You can access our privacy policy at Website Privacy Policy | Acara
Aleron companies (Acara Solutions, Aleron Shared Resources, Broadleaf Results, Lume Strategies, TalentRise, Viaduct) are an Equal Opportunity Employer. Race/Color/Gender/Religion/National Origin/Disability/Veteran.
Applicants for this position must be legally authorized to work in the United States. This position does not meet the employment requirements for individuals with F-1 OPT STEM work authorization status.
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