Senior AI/ML Engineer, CookUnity

• 5+ years of designing and building distributed back-end services in Kotlin (or Java) and modern TypeScript-based front-ends (React/Next.js)
• Ability to ship robust, production-grade Python code—owning everything from design and performance tuning to deployment
• Proven track record shipping LLM/GenAI features to production, with experience across the lifecycle: prompt engineering, fine-tuning, latency optimization, evaluation, and safety alignment
• Deep fluency with modern software delivery practices: test strategy, blue-green and canary deployments, observability, and rollback mechanisms
• Demonstrated experience driving adoption of automated testing strategies (TDD/BDD) and CI/CD best practices
• Strong written and verbal communication skills; ability to synthesize complex trade-offs for both technical and cross-functional stakeholders
• 10+ years of experience in AI/ML, data engineering, or related fields, with at least 3 years in a leadership role
• Proven experience leading cross-functional teams in an agile environment, with a strong ability to balance technical execution and strategic vision
• Expertise in machine learning algorithms, data pipelines, and AI/ML model deployment at scale
• Solid understanding of Large Language Models (LLMs) and Generative AI (GenAI), and how to integrate these technologies into business operations
• Strong understanding of cloud technologies (AWS, GCP, Azure) and modern data stack solutions (e.g., Apache Kafka, Snowflake, Redshift)
• Deep knowledge of data engineering best practices, including ETL processes, data warehousing, and data governance
• Strong communication skills, with the ability to clearly convey complex technical concepts to both technical and non-technical stakeholders
• Ability to drive change, inspire innovation, and foster a collaborative and results-driven team environment

Desirable

• We are seeking a Senior AI Engineer, Agent Orchestration to lead the development of next-generation agentic systems that infuse Generative AI into every layer of the software delivery lifecycle
• This is a hybrid role that blends full-stack engineering (Kotlin + TypeScript) with LLM systems design, focused on transforming developer workflows, CI/CD pipelines, observability, and runtime operations through AI-native automation
• As a technical spearheader, you will be responsible for architecting and scaling intelligent developer tools, copilots, and runtime agents that extend far beyond prompt engineering—enabling an accelerated, self-healing, and insight-driven engineering ecosystem
• Architect and deliver full-stack GenAI-integrated systems, leveraging Kotlin (Ktor/Spring), Python, React/TypeScript, and AWS tooling
• Operationalize LLMs and agent frameworks to automate SDLC stages: from requirements parsing and code generation to test synthesis, deployment validations, and post-deploy analytics
• Develop multi-agent orchestration patterns (e.g., tool use, planning, memory) across backend and frontend development flows
• Embed GenAI-driven workflows into developer tooling: Full Test Driven Development cycle, PR summarization, AI-assisted code reviews, and contextual documentation retrieval
• Extend CI/CD systems with LLM-based capabilities: dependency change impact prediction, and build-time telemetry analysis
• Instrument systems with DataDog and AI-native observability: anomaly detection, root cause localization, and natural language log exploration
• Partner cross-functionally with product, infra, and data teams to identify and prioritize AI-native engineering opportunities
• Scout, evaluate, and hands-on integrate cutting-edge GenAI frameworks and developer tooling—bringing innovative capabilities into our stack to radically streamline coding, testing, and deployment workflows
• Contribute to engineering-wide technical direction through architecture reviews, RFCs, and mentorship
• Lead, mentor, and develop a cross-functional AI/ML team, including data engineers and embedded data engineers
• Foster a community-driven culture that encourages knowledge sharing, collaboration, and continuous learning
• Align team objectives with broader company goals, ensuring that projects are executed effectively and efficiently
• Drive the development of scalable AI/ML solutions that support both operational and strategic goals at CookUnity
• Develop and implement machine learning models that improve customer personalization, operational efficiency, and data-driven decision-making
• Lead the integration and adoption of Large Language Models (LLMs) and Generative AI (GenAI) to enhance product features, improve customer experience, and accelerate business growth
• Stay at the forefront of emerging AI/ML technologies, including LLMs and GenAI, and apply relevant innovations to solve complex problems
• Oversee the architecture of CookUnity’s data pipelines, ensuring they are robust, scalable, and efficient to support machine learning, analytics, and GenAI model deployments
• Manage the end-to-end lifecycle of data processing, including ingestion, storage, transformation, and analytics
• Collaborate with the infrastructure team to ensure data platforms are optimized for performance, reliability, and security
• Work closely with product, engineering, and business teams to understand their data needs and deliver impactful solutions
• Drive the integration of embedded data engineering into core product development cycles
• Engage with senior leadership to align AI/ML strategies with broader company initiatives and business outcomes
• Establish and nurture a community of AI/ML experts across CookUnity to share best practices, solve challenges, and promote innovation
• Spearhead internal forums, workshops, and seminars to accelerate the adoption of LLMs and GenAI, ensuring that team members are up to speed with new technologies and trends
• Foster a culture of continuous learning and ensure the team is equipped to leverage the latest advancements in AI/ML
• Define and implement key performance indicators (KPIs) to track the success of AI/ML and GenAI solutions
• Present regular updates to the executive team, including the CTO, on project progress, challenges, and opportunities related to AI/ML and GenAI adoption