If you're interested in 2AI's work but none of our open roles feel like a strong fit, we encourage you to submit your information to our General Talent Pool.  We'll periodically review applications and reach out if we identify a role that may be a good match. Note that unlike our role-specific hiring rounds, we don't have a set review timeline or process, and we won't be able to provide status updates on General Talent Pool applications About The AI Access Initiative About The AI Access Initiative, incubated at Evidence Action  We're at an inflection point in artificial intelligence – presenting both tremendous potential opportunity and risk for people in developing countries: rather than allowing the poverty gap to expand, low-income countries have an opportunity to leapfrog development milestones with AI-powered innovations. Incubated at Evidence Action, we’re launching The AI Access Initiative, an organization focused on scaling AI-enabled ‘big bets’ to benefit tens or hundreds of millions of people in poverty in low- and middle-income countries (LMICs).  We will operate at the intersection of global development actors, top AI labs, and leading researchers to drive meaningful access to the benefits of AI for the 3.5 billion people living in poverty globally. We will create “public good,” open-sourced playbooks, toolkits, and insights that define how to design and launch tractable and impactful AI-enabled programs. Given the scale of opportunity, we expect our portfolio to expand substantially, but to start, we’re scaling two programs focused on AI in Agriculture and AI in Health. We are led by CEO Kanika Bahl, a founding member of Anthropic’s Long-Term Benefit Trust, and advised by Nobel Laureate Michael Kremer; Dario Amodei, CEO of Anthropic; and Kent Walker, President, Global Affairs for Alphabet and Google. This work builds on Evidence Action’s track record reaching 530M+ people with cost-effective, evidence-based programs across 9 countries in Africa and Asia, with a focus on last-mile delivery. Our Approach We’re building an AI-native organization focused on designing solutions to reach tens or hundreds of millions of individuals living in poverty. We will focus both on delivering near-term, tractable direct impact as well as assisting governments to grow capacity and build enabling environments for the AI for Good ecosystem, including:  - Scaling “big bet” AI interventions to impact tens or hundreds of millions, such as delivering AI-enabled forecasts to smallholder farmers to improve yields and earnings, leveraging AI to dramatically improve medical diagnosis and treatment, implementing frontier systems to identify and mitigate disease outbreaks, or putting personalized AI tutors into the hands of students to drive reductions to system-level educational attainment gaps. When relevant, we will partner with leading AI labs to shape technical offerings, including adapting for underrepresented languages, bandwidth constraints, etc. - Partnering with governments in low- and middle-income countries (LMICs) to drive regulatory changes, policy, and investments necessary to unlock beneficial use cases at national scale, while proactively mitigating the downside risks of AI. Building on our recent Cross-Sector Analysis of near and medium-term AI opportunities in LMICs, we are advancing the highest-scoring interventions through a rigorous vetting process, including evidence reviews, cost-effectiveness analyses, risk assessments, and early operational/technical scoping. We are excited about the opportunity to deliver AI-enabled weather forecasting for smallholder farmers, and are now running deeper analysis on opportunities in global health.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description At Firestorm, we are building autonomous aerial systems that operate where they are needed most, when they are needed most. Our mission requires speed, ingenuity, and a relentless commitment to engineering excellence. We move fast, test constantly, and deliver capability that performs in the real world, not just in simulation. We are looking for a Lead AI Software Engineer who is excited to build, test, and deliver production-grade AI-enabled software systems. This is a hands-on role, working on end-to-end delivery from early prototypes through hardened deployments. You will potentially lead a small team in the future. This role blends strong software engineering fundamentals with modern AI system development: - Turning ambiguous user intent into reliable, structured outputs - Integrating safely with existing internal systems - Building the validation, observability, and governance required for high-integrity environments This is not a research-only role. You will ship, iterate quickly, and set the technical and execution standard for a team operating under demanding timelines. If you want to build systems that matter, own your work end to end, and be part of a team that values bold thinking grounded in rigorous engineering, Firestorm is the place to do it. Qualifications - Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience) - U.S. Citizenship and the ability to obtain and maintain a U.S. Government security clearance - 8+ years of experience building and shipping production software systems (services, platforms, or distributed systems) - 4+ years of production AI/ML experience, including ownership of real-world reliability, safety, and performance outcomes - Demonstrated experience shipping LLM-enabled applications to production - Experience designing AI evaluation and quality gates - Experience operating AI systems in production - Strong proficiency in Python and at least one backend/systems language (e.g., Go, Java, C++, Rust) - Experience designing and evolving structured interfaces - Experience implementing safety/security controls for AI systems - Proven ability to lead execution in a fast-paced environment while staying highly hands-on - Excellent communication and documentation skills Requirements - Lead hands-on development of AI-enabled software systems from concept to deployment, balancing rapid iteration with engineering rigor - Support end-to-end delivery across product and engineering concerns: requirements intake, decomposition into structured outputs, validation, and release readiness - Build and maintain agentic workflows with clear safety and quality constraints - Define and enforce structured output contracts to reduce brittleness and enable long-term evolution - Establish build and release discipline - Drive operational readiness - Partner with adjacent engineering teams to integrate with existing platforms - Set team execution cadence - Identify high-risk failure modes in AI workflows and ship mitigations - Produce clear technical documentation and decision records Benefits - Comprehensive medical, dental, and vision plans - 401(k) Retirement Savings Plan - Equity grants for new hires - Unlimited PTO - Extremely generous company holiday calendar - Generous Parental Leave - Lifestyle Spending Account - FSA, DCFSA, HSA - Hospital Indemnity insurance - Critical Illness insurance - Accident insurance - Basic Life/AD&D, short-term and long-term disability insurance - Mental Health Resources available 24/7

• Architect compelling solutions utilising all aspects of the Power Platform and the wider Microsoft Ecosystem of Microsoft 365 and Azure. • Manage and complete the discovery, design, build, testing and deployment of solutions utilising the Power Platform and Microsoft Ecosystem. • Seamlessly integrate AI capabilities into business applications, utilising Copilot Studio, Azure AI Foundry and direct API access to different AI providers and models. • Translate editorial and operational needs into scalable, secure, and user-centric system designs. • Leverage large language models and AI-enabled services to design intelligent solutions, and support secure integrations with existing and third-party systems as required. • Lead multiple concurrent AI and automation projects from conception through to production delivery. • Coordinate internal resources, cross-functional teams, and act as the central point of accountability for project success.

• Diseñar, entrenar y optimizar modelos de Machine Learning y Deep Learning para resolver necesidades específicas de negocio • Implementar técnicas de fine-tuning y optimización de modelos generativos y LLMs • Desarrollar soluciones basadas en Retrieval-Augmented Generation (RAG) combinando recuperación de información con generación de contenido • Integrar modelos de IA en aplicaciones mediante APIs RESTful utilizando FastAPI • Diseñar e implementar estrategias de búsqueda semántica utilizando bases de datos vectoriales • Gestionar y optimizar vector databases para consultas de alto rendimiento • Participar en el diseño técnico, revisión de código y evolución de las soluciones de IA