Forward Deployed AI Engineer

Accion Labs; United States; Remote; USD 180,000 - 240,000; Part time

Job summary

Accion Labs is seeking a Fully Remote AI Engineer with 10+ years of experience to design and ship AI, automation, and data-platform systems. You will build data pipelines, ontology objects, and LLM-based applications, collaborating directly with business teams to turn prototypes into production workflows.

The role emphasizes production experience, security modeling, and ownership of measurable outcomes in financial services or asset-intensive contexts.

Qualifications

• Hands-on, production experience building and deploying workflows, pipelines, and ontology objects on Palantir Foundry or a comparable enterprise data platform.
• Practical experience building AI/ML and LLM-based applications — RAG pipelines, agentic/tool-calling workflows, and model evaluation.
• Strong software engineering fundamentals: clean pipeline/API design, version control, testing, and production deployment practices.
• Comfortable working directly with business users to translate requirements into working systems (embedded/forward-deployed engineering).
• Understanding of data security, access control, and governance patterns for enterprise data platforms.
• Clear technical communication — explain architecture, trade-offs, and status to engineers and non-technical stakeholders.
• Analytical mindset with focus on measurable ROI of what is built.

Responsibilities

• Design data pipelines and ontology within enterprise data platforms.
• Develop AI/ML and LLM-based applications and deploy them to production.
• Collaborate with business teams as an embedded Forward Deployed Engineer.
• Manage technical risk and measure outcomes of built systems.
• Ship AI, automation, and data-platform capabilities to internal operations.
• Ensure security modeling for data platforms and governance alignment.

Skills

AI/ML engineering

Data engineering

Forward-deployed engineering

LLM-based apps

RAG pipelines

Tool-calling workflows

Model evaluation

Software engineering fundamentals

Technical communication

Analytical mindset

Tools

Palantir Foundry

Databricks

Snowflake

PyTorch

TensorFlow

Hugging Face

Job description

Fully Remote - Forward Deployed AI Engineer - 12 months contract

Position Summary:

The AI/ML Engineer & Forward Deployed Engineer builds and ships the AI, automation, and Palantir Foundry systems that power our internal operations and initiatives. This is a hands-on, builder-focused role: designing data pipelines and ontology, developing AI/ML and LLM-based applications, and working directly and iteratively with business teams as an embedded Forward Deployed Engineer to turn prototypes into production workflows. The role also manages the technical risk and measurable outcomes of what it builds.

Experience:

Overall 10+ years of work experience

Minimum 5-7 years of hands-on experience in AI/ML engineering, data engineering, or forward-deployed/solutions engineering.

Demonstrated, production experience with Palantir Foundry is a plus (or a comparable platform such as Databricks or Snowflake) - pipeline building, ontology design, and security modeling.

2+ years of hands-on experience building and shipping LLM-based or generative AI applications (RAG, agents, tool-calling), and/or classical AI techniques such as natural-language processing, computer vision, or deep learning tools (PyTorch, TensorFlow, Hugging Face).

Track record of shipping AI, automation, or data-platform systems into production in a corporate or investment environment, not just prototypes.

Experience working directly with business or portfolio company teams in an embedded/consultative engineering capacity is a plus.

Experience in financial services, investment management, private equity, real estate, or other asset-intensive industries is preferred but not required.

Required Knowledge, Skills and Abilities:

Hands-on, production experience building and deploying workflows, pipelines, and ontology objects on Palantir Foundry or a comparable enterprise data platform (Databricks, Snowflake).

Practical experience building AI/ML and LLM-based applications — RAG pipelines, agentic/tool-calling workflows, and model evaluation.

Strong software engineering fundamentals: clean pipeline/API design, version control, testing, and production deployment practices.

Comfortable working directly and iteratively with business users to translate ambiguous requirements into working systems (forward-deployed / embedded engineering style).

Working understanding of data security, access control, and governance patterns for enterprise data platforms.

Clear technical communication — able to explain architecture, trade-offs, and status to both engineers and non-technical stakeholders.

Analytical mindset with a focus on measurable outcomes, performance, and ROI of what is built.