Senior AI Engineer
Role details
Job location
Tech stack
Job description
As a Senior AI/ML Engineer on the AI Experience team, you will play a critical role in designing, building, and operationalizing intelligent systems that enhance content discovery, personalization, search, editorial workflows, and audience experiences across VERSANT digital platforms.
You'll work with Python, Java, LangChain, AWS, OpenSearch, and a range of modern AI models to deliver scalable machine learning and generative AI capabilities. You will build services that support retrieval-augmented generation, semantic search, model integration, prompt orchestration, evaluation, and production-grade AI workflows.
You will contribute not only through strong engineering and applied AI expertise, but also through mentorship, architectural input, responsible AI practices, and a commitment to building reliable, measurable, and maintainable AI/ML-enabled products.
What We Value
Senior AI/ML Engineers at VERSANT go beyond model experimentation. They turn ambiguous business needs into practical AI solutions, mentor teams on sound ML and software engineering practices, and help shape a culture of responsible innovation. They partner across product, editorial, data, and engineering teams to deliver systems that are reliable, scalable, observable, and aligned with business priorities.
Responsibilities
Leadership
- Partner with product, data science, editorial, analytics, and design teams to define clear, practical AI and ML requirements
- Mentor engineers through architecture reviews, design discussions, code reviews, pairing, and onboarding
- Promote engineering, ML, and responsible AI best practices across the team
- Identify and solve systemic team issues that impact delivery, model quality, reliability, or operational excellence
- Participate in and help guide conversations around AI architecture, emerging model capabilities, search relevance, and media industry trends
- Champion a user-first mindset, advocating for AI solutions that improve content performance, editorial productivity, and audience experience
Technical
- Design and deliver end-to-end AI/ML services that support content intelligence, semantic search, recommendations, automation, and generative AI use cases
- Build and maintain production services using Python, Java, REST, and event-driven patterns
- Develop AI applications and orchestration workflows using LangChain and related frameworks
- Integrate with large language models, embedding models, multimodal models, and domain-specific AI services
- Design prompt engineering strategies, prompt templates, guardrails, and evaluation workflows for generative AI systems
- Use AWS services to deploy, monitor, secure, and scale ML-enabled applications and data pipelines
- Implement search, vector search, and retrieval-augmented generation patterns using OpenSearch and related indexing strategies
- Promote test coverage, model evaluation, secure development, and responsible AI practices
- Drive adoption of reusable AI platform patterns and help evolve shared ML engineering capabilities
- Debug, profile, and optimize model integrations, inference workflows, search relevance, latency, and cost
- Collaborate with SREs and platform teams to ensure AI services are observable, resilient, and production-ready
Delivery
- Scope large AI initiatives and epics; break down complex model, data, and platform problems into actionable tasks
- Proactively communicate risks, timelines, blockers, model limitations, and operational tradeoffs
- Balance competing priorities from editorial, product, data, privacy, security, and platform teams
- Support the team in achieving realistic delivery timelines while maintaining code quality, model quality, and sustainable velocity
Communication & Collaboration
- Partner across various teams to define and deliver cohesive AI-powered experiences
- Participate in technical hiring to help scale AI, ML, and platform engineering capabilities
- Create and maintain documentation for AI architectures, model integrations, prompt strategies, evaluation results, and operational runbooks
- Communicate technical decisions, model behavior, risks, and tradeoffs clearly to both technical and non-technical stakeholders
- Actively participate in post-incident reviews, model quality reviews, and cross-team discussions
Requirements
Do you have experience in System tuning?, Do you have a Master's degree?, Strong software engineering and applied AI/ML experience in large-scale, high-availability environments
- Proficiency in Python and Java for building production services, data workflows, and ML-enabled applications
- Hands-on experience with LangChain or comparable AI orchestration frameworks
- Experience integrating and evaluating a variety of AI models, including large language models and embedding models
- Deep understanding of prompt engineering, retrieval-augmented generation, semantic search, and model evaluation patterns
- Experience with AWS cloud services and production deployment patterns for AI/ML workloads
- Experience with OpenSearch, search relevance, indexing strategies, and vector search capabilities
- Proven ability to write secure, maintainable, testable code and operate services in production
- Experience working in agile teams with strong delivery and collaboration practices
- Strong understanding of observability, performance tuning, cost optimization, and operational reliability for AI systems
- Excellent problem-solving, debugging, analytical, and communication skills
Preferred:
- Experience in the media, publishing, streaming, advertising, or digital content industry
- Familiarity with content modeling, taxonomies, metadata, editorial workflows, personalization, and recommendations
- Experience with MLOps, model monitoring, feature pipelines, experimentation, A/B testing, or offline/online evaluation frameworks
- Master's degree in computer science, machine learning, data science, or equivalent experience
Benefits & conditions
Pulled from the full job description
- Tuition reimbursement
- 401(k)
- Health insurance
- Paid time off
- Vision insurance
- Dental insurance, At our Englewood Cliffs campus, you'll have access to:
- Free onsite fitness center and daily workout classes
- Gourmet cafeteria and fresh daily meal options
- Onsite services like dry cleaning and shoe repair
- Free shuttle service to/from Manhattan, Hoboken, and Jersey City
This position is eligible for company-sponsored benefits including medical, dental, and vision insurance, 401(k), paid time off, tuition reimbursement, and more.