AI Solutions Engineer II

About Us

Blueshift is the Intelligent Customer Engagement Platform (CEP), headquartered in San Francisco, that empowers leading B2C brands to drive truly personalized, 1:1 marketing across every channel. Founded by repeat entrepreneurs who previously built Mertado (acquired by Groupon) and were part of the early team at Kosmix (acquired by Walmart), Blueshift leverages AI, including Predictive, Generative, and Agentic AI, to automate customer engagement for clients like ClearScore, LendingTree, Udacity, and U.S. News. Backed by top-tier VCs including Nexus Venture Partners, Storm Ventures, and SoftBank Venture Asia, the company has raised a total of $65 million in venture funding and is consistently recognized as a market leader and a Deloitte Technology Fast 500 award recipient.

Blueshift is actively scaling its development center in Pune, India. As part of our team, you will drive innovation in cutting-edge technologies including machine learning, artificial intelligence, big data, and large-scale distributed data systems. This is an exciting career path for motivated individuals looking to build complex, impactful solutions that define the future of customer engagement.

AI Solutions Engineer II

As a Software Engineer in the AI Solutions team , you occupy a unique techno-functional position. You are not a researcher; you are an implementation specialist and problem-solver . You bridge the gap between our core AI infrastructure and real-world customer impact. You aren't just writing code; you are applying data engineering, analysis, and AI knowledge to help global brands realize the full potential of AI-driven marketing.

Responsibilities

• End-to-End Solution Delivery: Lead the full lifecycle of custom AI projects—from initial customer design and technical architecture to testing and production implementation.
• Production Stewardship: Take ownership of the "last mile" of delivery. This includes triaging technical tickets, analyzing logs (Datadog/Kibana), and debugging production issues in customer-specific AI workflows.
• Applied Data Engineering: Use SQL, Python, and Spark to transform disparate, messy customer datasets into clean, high-performing inputs for our AI engine.
• Stakeholder Collaboration: Partner directly with customer marketing teams and internal Product Managers to explain technical logic and ensure AI solutions meet business objectives.
• Cross-Functional Collaboration: Partner with the other teams across Blueshift to optimize data pipelines and debug distributed systems.
• Agentic Productivity: Integrate AI agents (like GitHub Copilot or custom internal agents) into the development lifecycle to accelerate code generation, testing, and debugging.
• Innovation & POCs: Develop Proof of Concepts (POCs) for AI experiments, benchmarking results to simplify and automate customer marketing ideas.