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Why this grade This listing scored 36/100, which is an F. It lost the most ground on freshness. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 0 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
-15 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
Full-Time Senior Software Engineering
The AI Enablement Team is the catalyst for internal transformation and product acceleration across Actian. In the modern data landscape, AI is not a siloed experimental lab; it is a core capability that must be embedded into our product DNA and our engineering workflows.
We are looking for an AI Enablement Lead who will architect, scale, and own our AI enablement strategy end-to-end. You are not a theoretical researcher or a passive prompt engineer; you are a highly practical, technical driver who builds the foundational platforms, tooling, and frameworks that allow other product and engineering teams to deploy AI safely, rapidly, and at scale. You will democratize AI across the organization, establish modern LLMOps/MLOps practices, and directly impact the Actian Data Intelligence Platform by introducing agentic workflows, intelligent data pipelines, and cutting-edge capabilities.
Core Responsibilities:
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Internal AI tooling: Design and maintain the core AI orchestration layers, centralized API gateways, and reusable frameworks (e.g., advanced RAG architectures, agentic frameworks) for company-wide consumption.
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Product AI Integration: Collaborate directly with core engineering teams to embed production-ready generative AI and machine learning features into the Actian Data Intelligence Platform.
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LLMOps & Governance Infrastructure: Establish strict guardrails, evaluation frameworks, and monitoring tools to track model performance, bias, data privacy, and security across all AI implementations.
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Cost & Latency Optimization: Actively monitor and manage cloud and API compute spend (token management, open-source vs. commercial models) and optimize execution latency for production AI features.
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Cross-Functional Upskilling: Lead workshops, design blueprints, and create documentation to empower non-AI engineering teams to build and maintain their own AI-driven features confidently.
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Rapid Prototyping (PoC to Production): Drive the engineering execution of high-impact AI proof-of-concepts, ensuring they are built with production-grade code that scales seamlessly.
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Standardization of Tooling: Define and enforce the organization's official AI stack, from vector database selection and vector embeddings strategies to semantic caching mechanisms.
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Vendor & Open-Source Strategy: Evaluate and manage partnerships with AI model providers and lead the technical assessment of cutting-edge open-source models to keep Actian at the vanguard of innovation.
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Data-Driven Impact Tracking: Define and track operational metrics for the AI Enablement function, such as developer adoption rates, reduction in time-to-market for AI features, and ROI of implemented AI tools.
Qualifications & Profile:
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Technical Background: Strong background as a Senior AI/ML Engineer, LLMOps Engineer, or Software Architect who has successfully built and scaled AI-powered applications in enterprise SaaS or complex data platforms.
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AI & Engineering Mastery: Deep technical expertise in Python or Go, semantic search, vector databases (e.g., Pinecone, Milvus, pgvector), orchestration frameworks (LangChain, LlamaIndex), and fine-tuning or prompt engineering of state-of-the-art Large Language Models (LLMs).
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Extreme Ownership: High-agency mindset. You don’t wait for product teams to ask for AI capabilities; you proactively build the frameworks that solve their bottlenecks before they even identify them.
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Software Engineering Rigor: You treat AI development as software engineering. You understand CI/CD, unit testing for AI (evaluation datasets), containerization (Docker/Kubernetes), and clean code architecture.
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Influence Without Authority: Exceptional leadership and communication skills. You can inspire and align disparate engineering teams around a shared technical vision without being their direct line manager.
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Communication: Exceptional verbal and written English communication skills. Ability to demystify complex AI anomalies or architectures into clear business value for internal stakeholders and executives.
What We Offer:
- The chance to be part of an innovative, fast-growing company making a significant impact in the data management space.
- Collaboration with a passionate and diverse team.
- Competitive salary and benefits package.
- Flexible work arrangements (remote or hybrid).
- Opportunities for professional growth and development.
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Where this listing came from
- 09 Jul 2026 Jobicy first sighting
Seen on 1 board over 65 days.