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1mo ago

Senior Principal AI Engineer

Vertex Pharmaceuticals Boston, MA

Boston, MA

1mo ago Closed

$188k - $282k/yr Full time Senior Agent Platform Ai Agent Platform

This position is no longer accepting applications (closed Sep 6, 2026).

Job Description

Vertex Pharmaceuticals is hiring a Senior Principal AI Engineer in Boston to design and scale shared agentic AI platform capabilities for production model integration and lifecycle management.

Responsibilities

Build/bring-your-own-agents capability (primary focus): create frameworks, SDKs, templates, interfaces, and guardrails so teams across Vertex can build, integrate, customize, and operationalize agents using shared platform standards
Platform services: deliver model integration, prompt and workflow orchestration, tool use, memory patterns, and agentic task coordination for other teams to build upon
Agent lifecycle and quality: implement agent registration, configuration, testing, deployment, versioning, monitoring, and retirement, plus evaluation and benchmarking frameworks
Developer experience ownership: enable self-service onboarding, documentation, reference implementations, and enablement resources to reduce time from concept to production
Standards and technical leadership: define platform APIs, service contracts, architecture patterns, and engineering practices that keep custom agents safe, reliable, and supportable
Architect and develop shared AI and agentic platform services for enterprise AI products and internal workflows
Own build/bring-your-own-agents systems that let teams create, register, integrate, deploy, and manage their own agents within the enterprise platform
Establish reusable SDKs, templates, interfaces, and guardrails to standardize agent build and onboarding
Define and deliver agent lifecycle capabilities including registration, configuration, testing, deployment, monitoring, versioning, and retirement
Build and maintain integrations with foundation models, model gateways, APIs, enterprise tools, and related AI infrastructure
Design and implement systems for prompt orchestration, workflow execution, tool use, memory patterns, and agentic task coordination
Develop reusable frameworks for evaluation, benchmarking, and validation of AI model, agent, and workflow performance
Establish observability capabilities including monitoring, tracing, logging, and alerting for AI workloads and autonomous agent interactions
Optimize performance, scalability, latency, reliability, and cost efficiency for production AI and agentic systems
Partner with product, data, engineering, security, and architecture teams to enable enterprise-ready AI solutions
Translate prototypes and experimental concepts into hardened, maintainable, production-grade services
Define engineering standards, best practices, and design patterns for AI platform development and deployment
Support governance, risk management, and responsible AI practices via measurable controls, policy enforcement, and technical safeguards for agent behavior
Drive platform adoption through reusable components, documentation, onboarding patterns, and developer enablement resources
Mentor engineers and provide technical leadership across AI platform initiatives
Evaluate emerging tools, frameworks, and architectural patterns in generative AI and agentic systems to inform platform strategy

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Machine Learning, Data Engineering, or a related technical field; advanced degree preferred
Significant industry experience in software engineering, machine learning engineering, or AI platform development, including experience in senior or principal-level technical roles
Proven track record designing and delivering production-scale AI or ML platforms
Strong experience building distributed systems, APIs, microservices, and cloud-native applications
Demonstrated experience operationalizing machine learning, generative AI, or agent-based solutions in enterprise environments
Experience designing extensible platform capabilities that enable internal teams to build or integrate custom applications, tools, or services
Deep understanding of software engineering best practices including testing, CI/CD, version control, code review, and system reliability
Deep understanding of AI-native software engineering practices, including establishing standards, governance, and best practices for responsible use of AI coding assistants and software engineering agents
Experience defining architecture, standards, and reusable services for large-scale enterprise environments
Experience leading complex technical initiatives and influencing architecture across cross-functional teams
Strong communication skills with the ability to explain complex technical concepts to varied audiences
Experience balancing experimentation speed with production engineering discipline, security, and maintainability

Technologies

APIs
Microservices
Cloud-native applications
CI/CD
Version control
AI/ML platforms
Foundation models
Model gateways
CLIs
Vector databases

Benefits

Eligible for an annual bonus and annual equity awards
Health insurance
Dental benefits
Vision benefits
Generous paid time off, including a week-long company shutdown in the Summer and the Winter
Educational assistance programs, including student loan repayment
Generous commuting subsidy
Matching charitable donations
401(k)
Overtime pay (in accordance with federal and state requirements, for some roles)

Preferred Skills

Advanced degree in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline
Experience with enterprise AI platforms, developer platforms, or internal tooling ecosystems
Experience building frameworks or platforms that support bring-your-own-component or extensible developer patterns
Developer experience focus, including self-service onboarding, SDKs, CLIs, sandboxes, templates, and documentation to reduce friction and accelerate time to first deployment
Familiarity with model gateways, retrieval-augmented generation, and evaluation frameworks
Experience implementing AI governance, responsible AI controls, and compliance-oriented technical solutions
Knowledge of vector databases, knowledge retrieval systems, and orchestration layers for intelligent applications
Experience in regulated industries such as biotechnology, pharmaceuticals, healthcare, or life sciences
Strong mentoring and technical leadership experience in highly collaborative environments
Ability to assess emerging AI technologies and translate them into practical platform capabilities

Pay Range

$188,000 - $282,000 per year

Location

Boston, MA (onsite)

AI Engineer

Optiver New York, NY

New York, NY

1mo ago Closed

$200k+/yr Full time Agent Platform AI Artificial Intelligence

This position is no longer accepting applications (closed Aug 31, 2026).

Job Description

Compensation

Salary: USD 200,000 per year

Responsibilities

Design, build, and deploy production-grade AI systems and products, including agent platforms, AI assistants, code review harnesses, evaluation frameworks, and agentic research pipelines, using Python and modern AI frameworks integrated with internal data platforms, external tools, and third-party AI services.
Evaluate foundation models, agent architectures, and AI workflows, making pragmatic technology decisions based on capability, reliability, latency, security, cost, and business impact.
Define success metrics and construct robust evaluation frameworks, benchmarking tools, and observability capabilities to measure AI quality, safety, performance, and production readiness while enabling continuous improvement.
Translate ambiguous business challenges into scalable technical solutions, ensuring AI-assisted development yields reliable software that meets functional requirements and business objectives.
Design resilient, distributed AI systems with a focus on scalability, state management, authentication, fault tolerance, security, and operational reliability.
Rapidly prototype and experiment with emerging models, tools, and workflows, validating new capabilities against measurable success criteria before investing in production.
Partner closely with trading, research, and business teams to understand user needs, challenge assumptions, rapidly iterate on solutions, and evolve successful use cases into reusable platform capabilities.
Deliver high-quality, maintainable software through sound software engineering practices, automated testing, and thoughtful code reviews.
Operate, monitor, and continuously improve production AI systems by optimizing quality, reliability, latency, cost efficiency, governance, and user outcomes.

Requirements

Bachelor's degree in Computer Science, Artificial Intelligence, or a related technical field
6+ years of professional software engineering experience, including extensive production experience developing applications in Python
Strong software engineering fundamentals, including software architecture, object-oriented design, design patterns, distributed systems, testing, and building scalable, resilient applications
Experience designing, deploying, and operating production LLM applications, with practical knowledge of model evaluation, prompt engineering, tool calling, context management, agent orchestration, and common failure modes
Experience defining evaluation frameworks and using quantitative metrics to guide model selection, prompt iteration, and production readiness
Experience integrating AI systems with external tools, APIs, Model Context Protocol (MCP), and modern AI application frameworks
Strong engineering judgment, with the ability to determine when AI is the right solution—and when traditional software or deterministic automation is more appropriate
Experience building highly reliable production systems where correctness, resiliency, observability, and operational excellence are essential
Strong product mindset, with the ability to translate ambiguous business problems into practical technical solutions that deliver measurable business outcomes
Excellent communication and collaboration skills, with experience partnering directly with cross-functional teams and end users to refine requirements, challenge assumptions, and deliver scalable solutions
Strong problem-solving skills and the ability to thrive in a fast-paced, dynamic environment

Technologies

Python
Model Context Protocol (MCP)

Benefits

The opportunity to work alongside world-class engineers and researchers from more than 40 countries
A highly competitive compensation package, including a performance-based bonus
A 401(k) match of up to 50%
Comprehensive medical, dental, vision, mental health, disability, and life insurance
25 days of paid vacation, plus market holidays
Extensive office perks, including breakfast, lunch, snacks, social events, clubs, sports leagues, and more

Who we are

Optiver's mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency, and stabilizing market conditions under diverse circumstances. As a leading market making institution, we are a trusted partner on more than 100 exchanges worldwide. Our differences are our edge, and Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, disability, or other protected characteristics.

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