Role Description We're looking for an experienced engineering leader to take ownership of Biorelate's engineering function. You'll have six direct reports, the leads of Platform Engineering (including Security), Data Engineering, and Full-Stack Engineering, with around 13 engineers across the function in total. You'll report to the VP of Technology. Most of your time will go into making the engineering organisation work well: - Clear ownership - Effective processes - Engineers who are growing - Projects that land on time You'll still stay close enough to the technical work to make good calls (architecture reviews, knotty production incidents, the occasional spike to de-risk a new direction), but your primary contribution is organisational. You'll be helping us execute against Biorelate's mission: accelerating drug discovery by building the world's largest and most accurate biomedical knowledge graph, and getting that data to the places where it has the most impact. What you'll own - The engineering function. - Technical leadership across three disciplines. - People development. - Engineering practice. - Delivery. Qualifications - 10+ years of engineering experience, with a meaningful chunk in data-heavy systems: pipelines, ML platforms, large-scale ETL, knowledge graphs, search, or analytics. - Significant time leading engineering teams or functions. - Experience in both startup and mature-company environments. - Credible across multiple engineering disciplines. - High tolerance for ambiguity. - Strong communication, written and verbal. - Curiosity about the domain and the customer. - Opinions about what good looks like. Requirements - You've run engineering organisations before, as a Head of Engineering, senior EM ready to step up, or equivalent. - You've felt the difference between "we need to ship this by Friday" and "we need a proper RFC process." - You've been somewhere long enough to see the consequences of your own decisions. - Depth in one of platform/infrastructure, data engineering, or application engineering. - Comfortable operating without perfect structure and helping to build it where it's missing. - Your instinct is to write things down, you're comfortable drafting a one-pager to explain a complex concept. - You should want to understand what our customers do with what we build. - You can articulate what distinguishes a well-run engineering organisation from a mediocre one. What we do Research and Development in the pharmaceutical industry is time-consuming, expensive, and often overlooks valuable data insights. We're changing that with AI-powered data science solutions that uncover hidden insights to support more efficient and informed drug discovery. Using AI-based Natural Language Processing, our technology extracts and structures data from millions of scientific documents, identifying causal biological relationships and organising them into knowledge graphs. This empowers bioinformaticians and biologists with a deeper understanding of the connections between diseases, proteins, and drugs. Our team consists of biomedical and data science experts with real-world lab and pharmaceutical experience. These specialists ensure that our solutions are scientifically grounded, delivering accurate, reliable data to our customers.

• Lead and grow the Identification Accuracy team — a multidisciplinary group of ML Engineers, Data Scientists, Analysts, and Analytics Engineers — fostering psychological safety, technical excellence, and a culture of continuous improvement. • Own the team's roadmap in close partnership with senior engineering leadership and cross-functional stakeholders, driving innovative solutions to identification-specific challenges and continuously raising the bar on model quality. • Drive model accuracy outcomes by enabling your team to design, train, evaluate, and ship ML models that improve identification accuracy at scale across billions of devices. • Build bridges across the organization — partnering closely with the Identification Engineering team (who operates the API your models power) as well as Product, and customer-facing teams to translate customer needs into technical priorities. Communicate effectively across technical and non-technical audiences, translating model performance and roadmap tradeoffs into language that resonates with business stakeholders and executive leadership.

• Criar e evoluir plataformas e sistemas de dados que possam ser usados por diferentes áreas da empresa; • Garantir que os fluxos de dados sejam seguros, escaláveis e resilientes; • Liderar a equipe na construção de pipelines (caminhos automáticos) para coleta, processamento e organização de dados entre nuvem e ambientes próprios; • Integrar soluções de dados entre áreas usando ferramentas modernas; • Implementar boas práticas de monitoramento, controle de custos e segurança dos ambientes; • Disseminar padrões técnicos, revisar códigos e apoiar a automação de processos; • Ser referência técnica para o time e para outros times da empresa.

Role Description The Manager, AI-Native Software Engineering leads a team of engineers building and maintaining the platforms that power Libra Solutions’ products within an agentic delivery model. This role combines people leadership with technical oversight, and is accountable for delivering high-quality software, growing the team’s AI-native capabilities, and ensuring the team operates effectively in a pod model where AI agents are active participants in the SDLC alongside human engineers. The ideal candidate is a player-coach who manages and develops a team effectively while staying connected to the technical work. They bring strong engineering depth in the Microsoft / Azure stack, proven people leadership skills, and demonstrated experience leading teams. This role partners closely with Engineering, Product, and business stakeholders to deliver high-quality software at scale. This position reports to the Director of Engineering and can be based in any of our office locations in Denver, CO, Huntersville, NC, Rosemont, IL or Las Vegas, NV. We welcome strong remote candidates, with occasional travel to Las Vegas as needed. Qualifications - Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent professional experience - 7+ years of professional software development experience - 2+ years of people management or team leadership experience - Strong hands-on background in C# / ASP.NET Core, Entity Framework Core, SQL Server / Azure SQL, and React or Angular - Experience with Azure DevOps, CI/CD pipelines, and cloud-native deployment practices on Azure - Experience partnering closely with engineering, product, and business stakeholders in an agile delivery environment - Demonstrated ability to lead, develop, and retain a high-performing engineering team - Strong problem-solving, communication, organizational, and coaching skills - Hands-on familiarity with AI-assisted development tooling (GitHub Copilot, Claude, Azure OpenAI) and a demonstrated commitment to building AI-native engineering practices - Experience leading teams within agentic or AI-accelerated delivery models, or a clear understanding of how agentic workflows change team rhythms, role expectations, and quality ownership Requirements - Manage, mentor, and develop a team of software engineers across all experience levels - Conduct regular 1:1s, provide timely and constructive feedback, and support each engineer’s professional growth and career development - Partner with recruiting to grow the team by attracting and hiring engineers aligned with the team’s AI-native technical direction - Set clear expectations, foster accountability, and build a culture of trust, collaboration, and continuous improvement - Address performance issues constructively and proactively - Own the team’s delivery commitments; ensure features, bug fixes, and technical investments are completed on time and meet quality standards - Participate in sprint planning, backlog refinement, and prioritization discussions with Product and stakeholders - Remove blockers, manage dependencies, and ensure the team has what it needs to execute effectively - Monitor and continuously improve team velocity, predictability, and delivery health within the agentic pod model - Maintain strong technical engagement: participate in architecture discussions, code reviews, and technical planning - Ensure the team adheres to engineering standards for C# / .NET, API design, database patterns, front-end development, and CI/CD using Azure DevOps - Identify and address technical debt; champion sustainable engineering practices - Drive adoption and effective use of AI-assisted development tools across the team - Partner with other engineering leaders to define and uphold organizational AI development standards, prompt engineering practices, and AI output review requirements - Track and evaluate team-level engineering metrics to identify systemic issues and drive continuous improvement - Use data to communicate engineering health, technical decisions, tradeoffs, and statuses clearly to stakeholders and leadership - Contribute to engineering-wide initiatives including hiring practices, standards, tooling, and process improvement Benefits - Competitive compensation - Medical, dental, vision, and life insurance plans - 401k match - Paid time off