Forward-Deployed AI Engineer

Acara Solutions, Inc.; Irving (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Acara Solutions is seeking a Forward‑Deployed AI Engineer to drive EBITDA impact across portfolio companies by deploying AI-powered automation and custom solutions. You’ll evaluate, select, and integrate third‑party AI platforms, build scalable automation, and train teams across a fast‑moving private equity environment.

You will work with Claude/Codex/Gemini platforms, LangGraph, LangChain and automation tools, ensuring data integrity and measurable outcomes within 30–60 days and beyond.

Qualifications

• 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.
• Experience in Private Equity, Management Consulting or Financial Services environments.

Responsibilities

• Third-Party Evaluation, Integration & Vendor Management: evaluate and select AI platforms; lead end-to-end implementation; run proofs of concept; manage vendor relationships.
• Measurement and ROI: define baselines and success metrics; translate results into EBITDA impact; provide progress updates.
• Custom Development & Deployment: design and build AI automation solutions; lightweight automations with no-code/low-code; develop extensions to third-party platforms; ensure production reliability.
• Enablement & Adoption: train portfolio teams; document deployments with runbooks and guides.

Skills

AI/ML systems

Python

Cloud platforms

LangChain

LangGraph

APIs & integration

CI/CD

Vendor evaluation

Tools

Claude Code

Claude Cowork

Codex

Gemini

Cursor

Windsurf

n8n

Zapier

Make

LangChain

LangGraph

Job description

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.

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.
• Apply 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 apply 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 apply 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

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.