AI Technology Lead

Straive is a global leader in enterprise‑grade Data Analytics and AI solutions, committed to empowering businesses across various industries with cutting‑edge technology and expert insights. Backed by EQT, a top private equity firm, we are uniquely positioned to drive innovation through significant investments and an entrepreneurial spirit. Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject‑matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities. With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective. Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT. Website: https://www.straive.com/ LinkedIn Job Title: AI Technology Lead Location: New Jersey- (Hybrid) We are seeking an AI Technology Lead to lead the delivery of GenAI-powered applications and data science solutions from concept through production. This role sits at the intersection of engineering, data science, and business, requiring strong project management discipline combined with hands‑on technical expertise. The ideal candidate can manage complex technical programs, guide a team of developers and data scientists, and actively contribute to solution design and development of GenAI solutions. Key Responsibilities Own end‑to‑end delivery of GenAI and data science projects, from requirements through deployment and post‑production support Translate business problems into clear technical scope, milestones, and delivery plans Manage project timelines, dependencies, risks, and issue resolution across multiple workstreams Drive Agile execution (Scrum/Kanban), including sprint planning, stand‑ups, reviews, and retrospectives Ensure delivery meets quality, security, compliance, and performance standards Act as a technical lead/partner to developers and data scientists Lead solution architecture and design, code reviews, and technical decision‑making; develop proofs of concept and rapid prototyping Guide implementation of GenAI applications, including LLM integration (OpenAI, Gemini, Claude, open‑source models), prompt engineering, RAG pipelines, embeddings, and vector databases; oversee model evaluation, guardrails, and responsible AI practices Mentor full‑stack development across frontend (React, Angular, or similar), backend APIs and services (Python, Java, Node.js, etc.), data pipelines, and feature engineering Partner with data scientists on model development and experimentation, MLOps/LLMOps workflows, deployment, monitoring, and retraining strategies Manage team and stakeholder relationships Qualifications Experience 10+ years of experience delivering technical projects in software engineering, data, or AI domains 3+ years leading projects involving AI/ML or GenAI technologies Proven experience managing engineering and data science teams Hands‑on experience delivering production‑grade applications, not just prototypes Technical Skills Strong experience designing and delivering solutions on Microsoft Azure Strong understanding of: Full‑stack application development Cloud platforms (Azure) APIs, microservices, and scalable architecturesSolid knowledge of GenAI concepts, including: LLMs, embeddings, vector search, RAG architectures Model limitations, hallucinations, evaluation techniquesExperience with data science workflows, MLOps, or LLMOps is highly desirable Comfortable reviewing code and contributing when needed Project Management Skills Experience managing complex, ambiguous problem spaces Excellent risk management and dependency tracking Ability to balance speed, quality, and technical debt#J-18808-Ljbffr