Staff Software Engineer

Job Description

We are seeking a skilled Software Engineer who will design, build, and maintain software systems that deliver business value. In this role, you will focus on code quality, architecture decisions, and reliable delivery while leveraging AI tools to enhance productivity. You will verify and review AI-generated code to ensure it meets our quality standards. In this forward-deployed role, you will be embedded directly with business units in R&D. You will operate like a "startup CTO," bridging the gap between building products and solving real business problems through rapid solution delivery and deep domain expertise. As part of the discovery-to-scale pipeline, you will identify recurring patterns and hand off validated solutions to Platform Engineers for generalization into enterprise capabilities. This role encompasses multi-team initiatives with organizational impact. You will set own direction within broader strategic goals, influence multiple teams and be recognized as a domain expert. You will handle very high complexity driving through ambiguity to deliver results.

Job Responsibility

Delivery: Lead technical delivery of complex projects across multiple teams, unblock others through hands-on contributions, ensure engineering quality
AI: Design AI-augmented engineering workflows for your area, evaluate new AI tools, train engineers on effective AI usage, balance speed with verification
People: Coach multiple engineers on career growth, lead hiring for technical roles across your area, shape team technical culture
Business: Drive business outcomes through technical solutions across your area, influence product roadmaps, partner effectively with business stakeholders
Process: Drive process efficiency within your team, coordinate cross-functional technical work, lead retrospectives
Documentation: Design documentation strategies for your projects, ensure knowledge persists beyond individuals, write specifications that enable effective collaboration

Requirements

Bachelor's degree in Computer Science, Engineering, or related field with 8-12 years of relevant experience
AI-Augmented Development: optimize AI tool usage, train engineers on AI-augmented workflows, evaluate new AI development tools, establish practices that balance AI speed with verification rigor
Business Immersion: rapidly acquire domain expertise, translate between business and engineering, mentor engineers on immersion
Data Integration: navigate complex enterprise data landscapes, build relationships to gain data access, handle undocumented schemas, build robust integration solutions, mentor engineers on data integration
Full-Stack Development: build complete applications rapidly across any technology stack, select the right tools, balance technical debt with delivery speed, mentor engineers on full-stack development
Multi-Audience Communication: influence through communication at all levels, handle difficult conversations skillfully, train engineers on effective communication, represent teams across the function
Problem Discovery: seek out undefined problems, embed with users to discover latent needs, coach engineers on problem discovery techniques, turn ambiguity into clear problem statements
Rapid Prototyping & Validation: lead rapid delivery initiatives, coach on prototype-first approaches, establish trust through consistent fast delivery, define clear criteria for prototype-to-production transitions
Site Reliability Engineering: define reliability standards, drive post-incident improvements systematically, design capacity planning processes, mentor engineers on SRE practices
Stakeholder Management: influence senior stakeholders, manage complex stakeholder landscapes with competing agendas, build trust rapidly with new stakeholders, shield teams from organizational friction
Team Collaboration: build high-performing teams, navigate complex interpersonal dynamics, foster psychological safety, create environments where diverse perspectives are valued
AI Evaluation & Verification: design evaluation frameworks for AI-generated code and content, test AI systems systematically, document limitations, ensure appropriate verification depth based on risk
AI Literacy: evaluate AI solutions critically, understand bias, fairness, and hallucination risks, make informed decisions about when AI helps vs when traditional approaches are better
Architecture & Design: design components and services independently for moderate complexity, make appropriate trade-off decisions, document design rationale, consider AI integration points in designs
Cloud Platforms: design cloud-native solutions, manage infrastructure as code, implement security best practices, make informed service selections, troubleshoot cloud-specific issues
Code Quality & Review: produce consistently high-quality, well-tested code, review AI-generated code critically, never ship code you don't fully understand, identify edge cases, ensure adequate test coverage
Developer Experience: design golden paths—opinionated, well-documented workflows developers can follow with minimal cognitive load, conduct user research, create self-service capabilities, build for Day 50, not just Day 1
DevOps & CI/CD: build complete CI/CD pipelines end-to-end, manage infrastructure as code (Terraform, CloudFormation), implement monitoring, design deployment strategies for services
Knowledge Management: design knowledge structures for discoverability, ensure knowledge accessibility across teams, facilitate knowledge sharing sessions, reduce single-person dependencies
Lean Thinking & Flow: optimize team processes systematically, measure and improve cycle time, remove bottlenecks proactively, deliver rapidly while maintaining quality
Pattern Generalization: extract reusable components from field solutions, design appropriate abstractions that balance flexibility with simplicity, collaborate with FDEs to validate generalized solutions in new contexts
Service Management: design service offerings with clear value propositions, manage service level agreements, improve service delivery based on user feedback, communicate service status proactively
Technical Debt Management: prioritize debt systematically based on risk and impact, balance debt reduction with feature work, make pragmatic trade-offs, know when to take on debt intentionally
Technical Writing: create comprehensive documentation for complex systems, write precise specifications that enable accurate AI-generated code, establish documentation practices for projects, ensure docs are discoverable

Pfizer - All Job Offers

Select Country

Staff Software Engineer – Forward Deployed

Job Description

Job Responsibility

Requirements

Looking for more opportunities?

Staff Software Engineer – Forward Deployed

Staff Software Engineer, Forward Deployed

Staff FullStack Software Engineer, (Forward Deployed), GPS

Staff Full-Stack Software Engineer, (Forward Deployed), GPS

Staff Forward Deployed Engineer

Senior Staff Software Engineer

Staff Software Engineer

Staff I Software Engineer - C# + Python

Our AI answers in your language