Staff Software Engineer - Internal Efficiency

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Software Engineer - Internal Efficiency based in United States.

This is a high-impact engineering role focused on transforming how internal teams work through AI-powered software and automation.

You will embed directly with teams across the organization to understand workflows, uncover bottlenecks, and identify opportunities for meaningful efficiency gains.

Rather than building solutions in isolation, you will own the full journey from discovery and prototyping to production, adoption, measurement, and iteration.

The role combines advanced software engineering with hands-on experience in LLMs, agentic systems, automation, and AI-assisted development.

You will have significant autonomy to decide where technology can create the greatest measurable impact.

Working across engineering, data science, product, security, design, and operational teams, you will turn ambiguous challenges into durable solutions.

Success will be measured not only by what you ship, but by the time saved, quality improved, throughput increased, and value created.

Accountabilities

• Embed directly with internal teams to understand workflows, map processes, identify bottlenecks, and prioritize high-leverage opportunities for AI-driven efficiency improvements.
• Translate ambiguous operational challenges into clearly defined technical solutions with measurable outcomes and success criteria.
• Own the complete software lifecycle, from discovery, requirements gathering, and rapid prototyping through production deployment, adoption, measurement, and continuous improvement.
• Design, build, deploy, and maintain AI-powered tools, agents, automations, and internal capabilities that improve how teams operate.
• Integrate AI solutions with Python- and Java-based microservices, web and mobile applications, internal systems, and third-party platforms.
• Drive adoption of agentic software development practices across engineering and help expand the organization’s technical capabilities through practical experimentation and knowledge sharing.
• Evaluate emerging AI models, tools, frameworks, and development patterns through rapid experiments, identifying approaches that can become reliable and scalable internal capabilities.
• Establish and monitor metrics such as time saved, throughput, quality, cost, and adoption to demonstrate the measurable impact of solutions.
• Communicate progress, results, trade-offs, and opportunities clearly to stakeholders and organizational leadership.
• Collaborate with engineering peers to develop, review, and refine technical architectures, designs, and implementation approaches.
• Partner closely with data science, product management, design, security, operations, and behavioral health teams to deliver solutions aligned with organizational needs.
• Promote high standards for software quality, security, reliability, and responsible AI development, particularly when working with sensitive data.
• Use strong technical and product judgment to determine where AI can meaningfully improve workflows and where conventional approaches may be more appropriate.

Requirements

• Bachelor’s degree in Computer Science or a related technical discipline.
• 8+ years of experience developing enterprise or consumer-facing web applications, preferably with strong experience in Python or Java/Spring.
• Hands-on experience building and deploying LLM-powered solutions in production environments, including agentic tools and frameworks, prompt engineering, context engineering, evaluations, and AI-assisted development workflows.
• Practical experience working with modern AI development tools and models, including Claude and Codex.
• Demonstrated ability to work directly with non-engineering stakeholders, uncover requirements, understand operational challenges, and translate ambiguous business problems into production-ready software.
• Proven ability to drive adoption of the solutions you build and demonstrate measurable improvements in organizational efficiency.
• Strong understanding of where AI can create genuine value and where its use may introduce unnecessary risk, complexity, or noise.
• Sound judgment when designing AI solutions involving sensitive information and high-impact operational or healthcare-related workflows.
• Strong software engineering fundamentals, including architecture, development, testing, deployment, and maintenance of production systems.
• Ability to collaborate effectively across engineering, product, design, data, security, and operational teams.
• Highly proactive and self-directed, with the confidence to identify opportunities and independently determine what should be built next.
• Comfortable operating with broad ownership and contributing beyond a traditional engineering role, including product thinking, design, quality, and technical strategy.
• Strong communication skills and the ability to explain technical concepts, trade-offs, and business impact to both technical and non-technical stakeholders.

Benefits

• Opportunity to work on high-impact AI initiatives designed to improve how teams operate and ultimately support better access to essential services.
• Significant autonomy and ownership over identifying problems, shaping solutions, and delivering measurable outcomes.
• Hands-on exposure to emerging LLMs, agentic systems, AI development workflows, and rapidly evolving technology.
• Collaborative environment with close partnerships across engineering, product, data science, design, security, and operational teams.
• Opportunity to influence the adoption of AI-assisted and agentic software development practices across engineering.
• Flexible work arrangement, with the option to work remotely from within the United States or from the South San Francisco, California headquarters in a hybrid capacity.
• Equal opportunity workplace committed to maintaining an inclusive and respectful environment.
• Opportunity to contribute to technology that supports meaningful outcomes for people and organizations.