Technical Staff Member – Forward Deployed

Chakra Labs

Forward-deployed engineer at Chakra Labs, building environments, evals, and datasets for frontier AI research. Owning customer deliverables from ambiguous research questions through production-ready platform capabilities.

Posted 8/12/2026full-timeBrooklyn • New York • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong full-stack engineering capabilities with proficiency in TypeScript and Python, focusing on translating research questions into actionable deliverables. Excels in communication with technical customers and researchers while managing project timelines and deliverables.

Highest-signal resume keywords

Full-Stack EngineeringTypeScript ProficiencyPython ProficiencyBackend Services DevelopmentData Pipeline Management

ATS Keywords

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Hard Skills

Full-Stack EngineeringTypeScriptPythonBackend ServicesData PipelinesFrontend DevelopmentTask DesignScoring Harness DevelopmentEvaluation SystemsDataset Creation

Soft Skills

Clear CommunicationCustomer Relationship ManagementProblem-SolvingChallenge Requests

Industry Keywords

AI ResearchProduction SoftwareTask SpecificationsGrading LogicValidation of Deliverables

Tech Stack

Tools & technologies

PythonTypeScript

About the role

Key responsibilities & impact

Take frontier AI research problems from an initial researcher hypothesis to a shipped deliverable
Build high-fidelity environments, evaluation systems, task distributions, grading logic, and datasets
Write environment code, task specifications, and scoring harnesses according to project needs
Identify one-off custom builds that should become generalized platform capabilities
Fold validated capabilities into the core product
Communicate with researchers and technical customers and challenge requests when appropriate
Translate loosely defined research questions into concrete environments, task sets, evaluations, or datasets
Validate that deliverables measure the intended capability rather than merely what is easy to build
Learn and apply task design, LLM-judged scoring, and reward-hacking detection
Own complete deliverables and customer relationships
Deliver projects to named customers and researchers under real deadlines

Requirements

What you’ll need

Strong generalist, full-stack engineering ability
Comfortable with backend services, data pipelines, and enough frontend development to ship a usable interface
Proficiency in TypeScript, Python, or similar languages
Ability to translate ambiguous research questions into concrete environments, task sets, evaluations, or datasets
Ability to validate that measurements assess the intended capability
Clear communication with researchers and technical customers
Ability to push back on inappropriate customer requests and identify underlying needs
Genuine interest in how agents fail and how to measure those failures
Ideally at least 3 years of experience shipping production software, though less experience may be acceptable
No ML research background required

Benefits

Comp & perks

Cutting edge: access to the latest technologies across the data, AI, and infrastructure stack
Work with a small team of experienced engineers from Stripe, Snap, AWS, Microsoft, and Airtable