Founding Member of Technical Staff

Location: San Francisco CA
Company Stage of Funding: Early Stage / VC-Backed
Office Type: On-site 6 days per week
Salary: $150000 $300000 Base
Equity: Generous Equity
Visa: Open to Visa Transfers including OPT and H-1B transfers
Experience: 2 years of professional software engineering or research experience; exceptional candidates with strong technical portfolios may also be considered
Employment Type: Full-time
Hiring Count: 12 candidates

Our client is an early-stage VC-backed AI company building technology that helps organizations make better decisions in complex high-stakes environments.

The company combines AI research software engineering data infrastructure and domain expertise to develop systems that can gather information analyze complex scenarios and simulate potential outcomes.

The engineering team is extremely small and highly autonomous. Engineers work directly with subject matter experts to identify important problems research novel approaches and turn those ideas into production AI systems.

This role sits at the intersection of software engineering and applied AI research. Engineers will work on data and AI infrastructure while also exploring techniques for simulating decision outcomes improving automated information gathering and applying reinforcement learning to AI systems.

This is an opportunity for an early-career or mid-level technical builder to have significant ownership work directly with technical and domain experts and contribute to both research and production systems from the ground up.

• Design and build the data and AI infrastructure supporting decision-focused AI systems.
• Develop automated data-gathering processing and analysis pipelines.
• Build reliable systems that allow AI models and agents to collect structure and analyze information at scale.
• Develop backend services and infrastructure supporting AI-powered workflows.
• Iterate quickly on new technical approaches and move successful experiments into production.

• Research new techniques for simulating the potential consequences of decisions.
• Explore multi-agent systems and model-based simulations.
• Investigate new approaches to automated reasoning information gathering and analysis.
• Prototype research ideas and evaluate their effectiveness through experiments.
• Translate promising research concepts into working AI systems.

• Build voice agents analysis agents and automated AI workflows.
• Design systems that allow agents to gather information and perform complex analysis.
• Develop multi-step agentic workflows for research and decision-support applications.
• Improve agent performance through experimentation evaluation and iteration.
• Build systems that can continuously improve how information is gathered and analyzed.

• Experiment with post-training techniques to improve AI model performance.
• Apply reinforcement learning techniques to AI systems and automated workflows.
• Design experiments that evaluate model and agent behavior over time.
• Work with PyTorch and modern machine learning tooling.
• Collaborate with subject matter experts to determine how AI systems should behave in complex real-world scenarios.

• 2 years of professional software engineering or research experience.
• Exceptional candidates with strong technical portfolios or significant personal projects may also be considered.
• Experience building software AI systems research systems or data infrastructure.
• Strong interest in applied AI research and experimentation.
• Demonstrated ability to independently investigate and solve difficult technical problems.
• Experience working in fast-moving environments with significant technical ownership.
• Comfortable moving between research experimentation and production engineering.
• Startup experience is strongly preferred.
• Candidates with approximately 35 years of experience can be particularly relevant for the more experienced profile.
• Early-career candidates with strong technical ability high initiative and exceptional projects can also be considered.

• Strong Python and/or TypeScript experience.
• Experience building production software or research systems.
• Strong understanding of software engineering fundamentals.
• Experience working with AI/ML systems.
• Experience with PyTorch is strongly preferred.
• Experience building data pipelines or automated analysis workflows.
• Familiarity with LLMs and modern AI systems.
• Experience with AI agents or multi-step AI workflows is a plus.
• Understanding of model training post-training or reinforcement learning is a plus.
• Strong ability to prototype and iterate on technical ideas.

• Strong interest in applied AI research.
• Experience experimenting with AI models and evaluating results.
• Understanding of agentic systems and multi-agent workflows.
• Experience with model post-training or reinforcement learning is strongly preferred.
• Familiarity with simulation reasoning or decision-modeling techniques is a plus.
• Ability to translate research concepts into practical software systems.
• Experience designing experiments and interpreting technical results.
• Comfortable working with uncertain or rapidly evolving AI technologies.
• Interest in improving AI systems through continuous experimentation and iteration.

• Extremely high agency and self-direction.
• Strong curiosity and intellectual flexibility.
• Comfortable working on open-ended research problems.
• Willing to investigate unfamiliar technologies independently.
• Strong builder mentality.
• Comfortable moving quickly from idea to prototype.
• Comfortable operating with incomplete requirements.
• Strong communication and collaboration skills.
• Comfortable working directly with subject matter experts.
• Excited by early-stage startup environments.
• Strong sense of ownership and accountability.
• Comfortable balancing research quality with practical execution.

• $150000 $300000 base salary depending on experience.
• Generous equity.
• Full-time employment.
• On-site work in San Francisco 6 days per week.
• Visa transfers supported including OPT and H-1B transfers.
• Health insurance.
• Catered meals.
• Significant ownership within a very small engineering team.
• Opportunity to work directly with technical and domain experts.

• Work at the intersection of AI research and production software engineering.
• Build novel AI systems from the ground up in an extremely early-stage environment.
• Research new approaches to simulation reasoning and decision modeling.
• Build AI agents and automated data-gathering workflows.
• Work directly with subject matter experts to turn complex problems into AI products.
• Experiment with reinforcement learning and model post-training techniques.
• Have substantial ownership over both research direction and production implementation.
• Work within a small team where individual contributions have significant visibility and impact.
• Move quickly from research idea to prototype to production system.
• Develop expertise across AI research agents data infrastructure and software engineering.