Role Description The AI Engineering Manager leads a cross-functional team (Development & QA) and owns technical architecture, delivery outcomes, AI-enabled system design and driving an AI first culture among your team. This role is both strategic and hands-on. It requires strong expertise in modern AI frameworks, applied AI architectures, and scalable system design. The manager is accountable for delivering stable, secure, AI-powered capabilities — not just managing execution. Core Responsibilities - Technical Leadership & Architecture - Own product architecture, including AI/LLM-integrated components - Design scalable, secure, and maintainable systems - Lead decisions involving: - LLM integration (OpenAI, Azure OpenAI, etc.) - RAG architectures and vector databases - AI orchestration frameworks (LangChain, Semantic Kernel, LlamaIndex) - Ensure system reliability, observability, and cost efficiency - Establish AI governance and safe usage practices - AI Framework & Methodology Expertise - Apply modern AI methodologies, including: - Retrieval-Augmented Generation (RAG) - Prompt engineering and evaluation - AI output validation and guardrails - Human-in-the-loop workflows - Model monitoring and performance evaluation - Drive experimentation, A/B testing, and telemetry-based decision making - Team Leadership - Lead and mentor developers and QA engineers - Raise AI literacy across the team - Establish AI-native coding and review standards - Balance speed, quality, and architectural integrity - Delivery & Outcome Ownership - Own predictable, high-quality releases - Ensure AI features are measurable, validated, and production-ready - Act as technical escalation point - Drive cross-team alignment with Product, Data, and DevOps - AI-Driven Engineering Excellence - Leverage AI-assisted development tools to improve velocity - Optimize AI cost-performance tradeoffs - Embed automation into testing and CI/CD pipelines Qualifications - 7+ years software engineering experience, 2+ years in technical leadership - Hands-on experience building and deploying AI-enabled systems - Strong knowledge of: - LLM integration and prompt design - RAG architectures and vector search - AI orchestration frameworks - Cloud platforms (Azure, AWS, or GCP) - Experience designing scalable distributed systems Preferred - Experience in regulated industries - AI governance and compliance knowledge - Model lifecycle management and monitoring tools Company Description Anju Software delivers end-to-end solutions for the life sciences industry, supporting clinical trials, medical affairs, and scientific data management with precision, compliance, and operational rigor. Our products help pharmaceutical, biotech, and medical device companies bring therapies to market faster and more efficiently. Anju is part of Valsoft Corporation, a global acquirer and operator of vertical market software businesses. Valsoft invests with a long-term mindset, empowering each company to operate autonomously while benefiting from shared capital and operational expertise. We are entering a new phase of growth, focused on embedding AI deeply into our systems and workflows. We are excited to add talent who will help lead our transformation into a truly agentic, automation-driven organization that redefines how work gets done in life sciences.

We're hiring an Engineering Manager for the Catalog team — the system of record for every product sold on the platform. The team owns the product data model, taxonomy and attribution, data quality, and the browse and filtration experience that turns catalog data into discovery. This is a player-coach role. You'll manage a team of engineers — hiring, growing, and holding the bar — while staying hands-on enough to review schemas, challenge query plans, and shape architecture through written RFCs rather than by taking delivery work yourself. Catalog reads sit on the hottest path of every storefront request, and catalog data quality directly drives filtration depth, feed approval, SEO eligibility, and merchant GMV. You'll be expected to lead through earned authority: influence built on judgment, consistency, and care — not the reporting line. **What You'll Own** **Product Data & Attribution** - The catalog data model — products, variants, media, pricing, availability — correct on write, fast on read, at the scale of merchants running 100k+ SKUs on shared infrastructure - Attribute architecture: category-scoped schemas, multilingual values, merchant-defined custom fields - Coexistence of merchant category trees with a canonical platform taxonomy - Data quality as a measurable system: completeness scoring, identifier coverage, enrichment loops that lift feed approval and conversion **Filtration & Indexing** - Faceted navigation with accurate counts, category listing performance, sort/ordering at scale - The pipeline from product mutation to searchable document — event-driven updates, freshness SLAs, zero-downtime reindexing - The index contract that relevance is built on, in partnership with the Search team (who own query-side ranking) **What You'll Manage** - Own hiring end-to-end; raise the bar with every offer - Build growth plans tied to the domain's hardest problems; run honest performance management, difficult conversations included - Protect the team's focus — predictable scoping and sequencing, and the willingness to say no with reasons - Own the tech-debt roadmap as a standing capacity allocation, backed by postmortems and engineering health metrics - Own incident response and observability of the domain itself — feed rejection rates, index lag, facet latency, not just server health - Partner daily with Product, Storefront, Search, and channel-feed teams

Role Description Fanatics Betting & Gaming (FBG) is seeking a Senior Manager to lead our Platform Engineering team in the US. This position plays a critical role within the Platform Engineering organization, partnering closely with teams across the United States, UK, and Ireland to own and operate the platforms that power Fanatics Betting & Gaming’s global software ecosystem. As a Senior Manager, you will own technical delivery, team growth, and operational excellence across areas such as: - Cloud infrastructure (AWS/Kubernetes) - CI/CD and release engineering - Observability - Developer tooling The platform has moved past its 0–1 phase; the focus now is on second-order, high-leverage problems: - Developer experience at service-sprawl scale - Intelligent AI integration into existing workflows - Durable architectural improvements that compound over time Qualifications - Proven experience directly managing platform engineering teams (not solely adjacent teams such as database enablement or generalist backend teams) - Strong hands-on background with cloud infrastructure (AWS), Kubernetes, and CI/CD / release engineering - Demonstrated people-management strengths: coaching and mentorship, performance management, and fostering psychological safety - Experience in building and communicating a multi-quarter strategic roadmap for a platform organization Requirements - Champion a “platform as a product” mindset — treat internal developers as customers, gather feedback, and prioritize based on developer experience (DevEx) impact - Own operational excellence for the team's services: on-call philosophy, incident response, and blameless post-mortems - Evaluate build-vs-buy decisions for internal tooling versus third-party SaaS solutions - Operate within a regulated environment — ensure delivery speed does not compromise compliance or security requirements - Evaluate and help roll out AI-assisted engineering tools across the distributed team without compromising security - Communicate platform health, roadmap, and outcomes clearly to engineering leadership and stakeholders Benefits - Salary Range: $190,080 — $237,600 USD - For information about our benefits, please visit https://benefitsatfanatics.com/

Role Description Nebula is KLDiscovery’s flagship eDiscovery platform: a cloud-based SaaS product that carries legal teams from data ingestion through early case assessment, review, and production. With Nebula AI capabilities such as ECAi early case assessment, document summarization, and PII and PHI detection now central to the roadmap, the engineering organization behind Nebula is entering its most ambitious phase yet. The Director, Software Engineering owns delivery for that organization. Leading managers and a team of engineers, this role is accountable for: - Shipping the Nebula roadmap predictably. - Keeping the platform fast and reliable at scale. - Building the team that does both. The role reports to the EVP, IT and Engineering and partners daily with Product, Design, and the senior leadership team. Job location: Remote (but candidate must be based in the United States) Key Responsibilities - Delivery and execution: Run the Nebula development lifecycle end to end: quarterly planning, sprint execution, release management, and post-release quality. Set and track engineering metrics such as cycle time, escaped defects, and availability, and use them to raise predictability rather than to police teams. Surface risk early and remove roadblocks so teams can stay focused. - Cloud platform and scale: Advance the platform architecture with your senior engineers: multi-tenant scalability, performance on very large data volumes, cost efficiency, and the reliability clients expect from a system entrusted with litigation data. Sponsor modernization work in areas like service architecture, infrastructure automation, and observability, and balance it honestly against feature delivery. - AI capabilities: Partner with Product and applied research to take AI features such as ECAi, summarization, and sensitive-data detection from prototype to production quality, including model evaluation, guardrails, cost control, and the security and privacy review that legal-sector clients demand. - People leadership: Hire, coach, and grow engineering managers and senior individual contributors. Own org design, performance management, career development, and succession for the group, building a team where senior talent is well leveraged and junior talent has room to grow. - Partnership: Act as the engineering voice for Nebula with executives, Product Marketing, and Client Services, and occasionally with clients and prospects. Translate 12 to 18 month business objectives into a technical strategy the teams can execute. - Planning and budget: Own headcount planning, third-party technology relationships, and the engineering budget for the group, with monthly forecasting and variance reporting. Qualifications - 10+ years in software engineering, including 5+ years managing engineers and experience managing managers. - A track record of shipping and operating commercial SaaS products on a major cloud platform. - Experience delivering AI- or ML-powered product features to production, or close partnership with teams that did. - Fluency in modern delivery practice: agile at scale, CI/CD, automated testing, and observability. - Demonstrated success hiring and developing engineering leaders in a remote or distributed organization. - Clear, direct communication with executives and non-technical stakeholders. - A bachelor’s degree in computer science or a related field, or equivalent practical experience. Nice to Have - Experience in eDiscovery, legal technology, or another regulated, data-intensive domain. - Familiarity with large-scale search and document-processing pipelines and with SOC 2 or ISO 27001 environments. Benefits - Competitive total compensation that includes base pay, bonus potential, inclusive benefits, wellness programs, and perks. - Market and industry data to inform pay decisions while considering geography and labor markets, individual experience, and business needs. - Individual compensation will vary, although a reasonable estimate of the current annualized base pay range for this position is $190,000 to $225,000.