Lead technical and people leadership for AI engineering and data science teams, translating business needs into scalable AI solutions across commercial operations.
Locations (2)
Horsham, Pennsylvania, United States
Titusville, New Jersey, United States
Compensation
The anticipated base pay range for this position is $137,000 and $237,500 USD.
Responsibilities
Provide hands‑on technical leadership for design, engineering, integration, and delivery of scalable AI and agentic solutions
Serve as a technical bridge across Data Science, business stakeholders, architecture, engineering/platform teams, AI platform teams, and external partners
Translate business and Data Science requirements into scalable, enterprise‑ready technical solutions
Lead AI solutions from prototype through integration, deployment, and ongoing enhancement
Advance reusable engineering approaches that enable AI capabilities to scale across brands, therapeutic areas, and commercial use cases
Requirements
Ph.D. in Computer Sciences, Statistics, Machine Learning & Artificial Intelligence, Physics, Molecular Biology, Bioinformatics, Computational Informatics, Medical Informatics, Computational Biology or a related quantitative field
M.S. with 10+ years of commercial pharma experience
Lead the design, development, and implementation of enterprise AI solutions, serving as the subject matter expert for AI initiatives across manufacturing data, enterprise copilots, and governed AI capabilities.
Responsibilities
Design, develop, operationalize, and deploy AI/ML and LLM-based solutions in production
Build data pipelines and integrations to support AI use cases
Implement enterprise AI architectures, including RAG, vector databases, semantic layers, orchestration frameworks, and AI assistants
Work directly in code, including Python, APIs, and cloud services, to deliver end-to-end solutions
Understand business issues, value, requirements, and success criteria
Requirements
Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering (or a related field), or equivalent practical experience
Working at the intersection of applied AI, commercial problem-solving, and business transformation, you will help turn high-value opportunities into practical AI solutions that transform how commercial teams operate.
Responsibilities
Work directly with PHB commercial teams to understand workflows, user needs, and business challenges, translating them into practical AI solutions.
Design and build AI agents, applications, and workflows utilizing prompting, grounding, retrieval, tool usage, actions, and orchestration.
Develop thin-slice solutions to rapidly validate user value and technical feasibility.
Build iteratively with users, leveraging feedback and evidence to improve, redesign, or discontinue solutions where appropriate.
Securely connect AI solutions to enterprise platforms and data sources, including Salesforce, Microsoft 365, and approved AI services.
Requirements
Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience
Staff Data Scientist with strong Machine Learning foundations and practical enterprise experience to join the VMDR team.
Responsibilities
Drive complex AI and ML initiatives through the full product lifecycle from early-stage prototyping and deep domain analysis to production-grade deployment and monitoring
Design and build production-ready AI models and system pipelines in Python using modern cloud and big data infrastructure (AWS, Spark)
Integrate state-of-the-art Generative AI and LLM workflows directly into our core VMDR features to drive automated detection, prioritization, and remediation insights
Partner closely with domain researchers, data engineers, and product leaders to dive into granular cybersecurity data and translate complex security problems into high-impact AI solutions
Requirements
M.Sc. or Ph.D. preferred or equivalent research experience
Lead Avalo’s enterprise AI and data transformation strategy, building systems, pipelines, and governance to drive value across R&D, commercial, and operational functions.
Responsibilities
Own and execute AI and data transformation strategy, roadmap, and investment plan
Establish and manage AI initiative portfolio with transparent intake and prioritization
Advise senior leadership on AI opportunities and strategic implications
Lead company-wide adoption of approved AI tools and build AI literacy
Define business requirements for data products, pipelines, and AI solutions
Requirements
Bachelor's degree in computer science, data science, engineering, life sciences, or related fields
Partner with Account teams and practice Customer Engineer (CEs) during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDE engagement requests.
Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks.
Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.
Requirements
Bachelor’s degree
Nice to have: orchestrating specialized technical resources
Nice to have: presenting to technical stakeholders
Enterprise architect, technical debugger, engineering liaison and technical delivery manager for AI solutions at Google Cloud.
Responsibilities
Partner with Account teams and Practice Customer Engineer during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDE engagement requests.
Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks.
Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.
Requirements
Bachelor’s degree or equivalent practical experience
Nice to have: deep technical problem solving
Nice to have: diagnosing bugs
Nice to have: executive communication
Nice to have: presenting to technical stakeholders or executive leaders
Solutions Engineer with strong Informatica platform experience and deep automation and integration engineering expertise to design, architect, and deliver end-to-end solutions that enable an enterprise data marketplace and broader data platform capabilities.
Responsibilities
Architect end-to-end data marketplace and data platform integrations spanning Informatica products and non-Informatica enterprise tooling
Design scalable, secure, and reliable architectures with an automation-first and integration-by-design mindset
Define reference architectures, integration patterns, and extensibility models for marketplace, metadata, governance, and data product use cases
Design and implement solutions using Informatica capabilities such as data integration, metadata management, data catalog, governance, data quality, and automation services
Configure and extend Informatica platforms to enable automated data product onboarding, discovery, lineage capture, access workflows, and marketplace interactions
Lead AI Engineer responsible for designing, building, and shipping generative AI systems and agentic solutions for Bain’s clients.
Responsibilities
Contribute to the design, development, and deployment of end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.
Build and iterate on multi-component AI pipelines such as Retrieval-Augmented Generation, fine-tuning, embedding generation, hybrid retrieval strategies, reasoning, tool use, and orchestration across AI workflows.
Build and contribute to agentic systems, applying sound engineering principles around separation of concerns, memory architecture, and tool integration.
Contribute across the full stack: model experimentation, evaluation design, and production system deployment.
Build and maintain APIs, microservices, CI/CD pipelines, and cloud-native deployments with attention to observability and reliability.
Requirements
Nice to have: French language proficiency at C1 level or higher
Nice to have: experience mentoring peers
Nice to have: experience with ReAct, RLAIF, and other HITL + feedback loops
Nice to have: experience with hybrid or graph-based retrieval approaches
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