As Director/TL, AI Capability Architecture Lead, you will lead the Enterprise AI Capability Design Team, accountable for designing, building, and evolving modular, reusable AI capabilities (SDKs/modules) that can be embedded into application backends or consumed as platform services with feature parity. You will manage a team of Software Engineers and DevOps Engineers, and you will include/principally mentor an AI Architect (IC) who co‑drives high‑bar technical design. Your scope spans capability roadmap stewardship, API/SDK design and versioning, quality engineering and evaluation, observability-by-design, and secure-by-default patterns that the Platform team can extend into microservices and managed services.
You will ensure these capabilities are extensible, composable, and performant, and that they integrate cleanly with enterprise controls and telemetry. You will partner closely with the Platform team (for service implementation), the Embedded AI Architecture Team (for solution patterns and field feedback), AI Engineering (for model/agentic expertise and rotation), and AI Architecture Operations (for process, metrics, and documentation standards).
Why this Role Matters
This is the productization engine for reusable AI. By turning proven patterns (e.g., RAG, document intelligence, agentic workflows, evaluation harnesses, prompt tooling, safety filters) into well‑engineered SDKs/modules, you multiply delivery velocity across business products while raising quality and safety. Clear SDK↔Service parity, rigorous testing and evaluation, and developer‑first DX reduce bespoke one‑offs, lower total cost of ownership, and make AI features operable at enterprise scale. You create the building blocks that embedded architecture and product teams can adopt with confidence.
Candidate Profile
You are a hands‑on architectural leader who blends deep software engineering with AI capability design. You are fluent in API/SDK design, packaging/versioning, performance engineering, and security-by-design, and you know how to translate applied AI methods into composable, testable, observable modules. You are passionate about developer experience (DX), you maintain high code and documentation standards, and you thrive in cross‑functional, matrixed environments where platform alignment and reuse are paramount.
ROLE RESPONSIBILITIES
1) Capability Ownership & Technical Direction
- Help define and own the capability portfolio and roadmap (e.g., RAG components, document intelligence, evaluation toolkits, prompt and safety utilities, agent tooling, vector/connectors, feature stores, model/endpoint clients).
- Drive API and SDK architecture: consistent patterns, semantic versioning, backward compatibility policies, error models, dependency rules, and language support strategy.
- Ensure SDK↔Service parity: author service interface contracts and service readiness specs (SLOs, scalability envelopes, observability and security controls) for Platform implementation.
- Establish reference implementations and exemplars that demonstrate correct integration, performance envelopes, and guardrail usage.
2) Engineering Quality, Testing & Evaluation
- Make rigorous testing non‑negotiable: unit, integration, contract, fuzz/adversarial, performance/regression, and security tests wired into CI/CD.
- Embed AI‑specific evaluation: datasets, metrics, harnesses, red‑teaming hooks, and reproducibility standards (seeds, data/version pins).
- Define quality gates for release: evaluation coverage thresholds, latency/throughput budgets, cost envelopes, security/privacy checks, and documentation completeness.
- Partner with AI Engineering to validate model‑ and agent‑level behaviors and to capture failure modes and mitigations.
3) Observability, Security & Compliance by Design
- Bake in telemetry and diagnostics: structured logs, traces, metrics, and debug hooks that flow to enterprise observability stacks; define SLIs/SLOs and error budgets.
- Lead threat modeling and security controls (authn/z, secrets, key management, data minimization, PII handling, abuse safeguards, rate limiting).
- Own supply chain hygiene: SBOMs, artifact signing, dependency policies, license scanning, and vulnerability management; align to internal standards (e.g., SLSA‑like controls).
- Ensure documentation and evidence support auditability (compliance, privacy, and regulated-context expectations).
4) Developer Experience (DX) & Enablement
- Set the DX bar: quickstarts, sandbox projects, code samples, "10‑minute Hello World," and task‑focused guides.
- Maintain API docs and design narratives with Technical Writers (via Operations): diagrams, ADRs, changelogs, and deprecation notices.
- Run capability showcases and office hours; capture field feedback and close the loop into the roadmap.
5) Cross‑Team Collaboration & Reuse
- Partner with Embedded AI Architecture to translate solution patterns into reusable capabilities; close gaps discovered in product engagements.
- Partner with Applied AI Engineering department for the development of PI of the SDKs.
- Co‑design service boundaries and readiness with the Platform team; ensure consistent operability, security, and cost/performance characteristics.
- Coordinate with Operations Excellence on playbook alignment, artefacts, and KPI instrumentation; publish regular capability health reports.
- Support rotation programs with AI Engineers/Software Engineers to broaden expertise and pipeline future capability owners.
6) People Leadership & Org Health
- Lead, coach, and performance manage Software Engineers and DevOps Engineers; mentor the AI Architect (IC) as technical bar‑raiser.
- Define competency models and growth paths (architecture, performance, reliability, security, evaluation) with Operations Excellence.
- Foster a culture of clean design, measurable quality, and documentation excellence; celebrate reuse and contributions across teams.
7) Tooling, CI/CD & Release Management
- Own the build and release system for SDKs/modules: pipelines, artifact repositories, package registries, versioning, and release trains.
- Automate quality gates and evidence capture in CI/CD (evaluation reports, perf baselines, SBOMs, test coverage).
- Define deprecation and migration policies; provide safe upgrade paths and tooling (linters, codemods, compatibility shims).
BASIC QUALIFICATIONS
- 10+ years in software architecture/engineering with significant experience building SDKs/libraries/platform modules and partnering with platform/service teams.
- Demonstrated ownership of API/SDK design, semantic versioning, compatibility strategies, packaging, and cross‑language delivery.
- Proven track record instituting rigorous testing and evaluation, including performance engineering and security controls for AI‑enabled components.
- Experience designing for observability (SLIs/SLOs, tracing/metrics/logging) and establishing release quality gates in CI/CD.
- Exceptional communication skills; able to align architects, platform engineers, and product stakeholders around capability roadmaps and standards.
PREFERRED QUALIFICATIONS
- Hands‑on familiarity with GenAI/LLM ecosystems (prompt tooling, RAG strategies, vector stores, agent frameworks, evaluation tooling) and traditional ML integration patterns.
- Background in cloud‑native architecture: microservices, eventing/streaming, APIs, containers/orchestration, and cost/performance optimization.
- Experience in regulated or high‑assurance environments (healthcare, pharma, finance) and audit‑ready documentation/change control.
- Exposure to MLOps/LangOps stacks, policy/guardrail integration, and data governance patterns relevant to AI capabilities.
- Demonstrated leadership building developer experience programs (docs, samples, trainings) and running open‑source‑style contribution workflows internally.
Work Location Assignment: Hybrid
Purpose
Breakthroughs that change patients' lives... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives.
Digital Transformation Strategy
One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.
Flexibility
We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let's start the conversation!
Equal Employment Opportunity
We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms - allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.
Disability Inclusion
Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career. Your journey with Pfizer starts here!
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What We Do
Our purpose ensures that patients remain at the center of all we do. We live our purpose by sourcing the best science in the world; partnering with others in the healthcare system to improve access to our medicines; using digital technologies to enhance our drug discovery and development, as well as patient outcomes; and leading the conversation to advocate for pro-innovation/pro-patient policies.
Why Work With Us
We are the inventors, the problem solvers, the big thinkers — those who surmount any hurdle to deliver breakthrough medicines to the people who are counting on them the most.
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Employees engage in a combination of remote and on-site work.







