AI Solution Engineer

We are looking for an experienced and innovative AI Solution Engineer to join our team and push the boundaries of large language model (LLM) technology to have significant impact on our products. In this role, you will leverage your strong software engineering skills (particularly in Java and cloud-based backend systems) and your hands-on experience with cutting-edge AI (LLMs, prompt engineering, to build intelligent features for enterprise (B2B SaaS). As an AI Engineer on our team, you will design and deploy AI-driven solutions (such as LLM-powered agents and context-aware systems) from prototype to production, iterating quickly and staying up to date with the latest developments in the AI space. This is a unique opportunity to be at the forefront of a new class of engineering roles that blend robust backend system design with state-of-the-art AI integration, shaping the future of user experiences in our domain.

Key Responsibilities

• Design and Develop AI Features: Lead the design, development, and deployment of generative AI capabilities and LLM-powered services that deliver engaging, human-centric user experiences . This includes building features like intelligent chatbots, AI-driven recommendations, and workflow automation into our products.

• Build LLM-Based Agents: Develop and refine LLM-based agentic systems that can autonomously perform complex tasks or assist users in multi-step workflows. Incorporate tools for planning, memory, and context management (e.g. long-term memory stores, tool use via APIs) to extend the capabilities of our AI agents. Experiment with emerging best practices in agent design (planning algorithms, self-healing loops, etc.) to make these agents more reliable and effective.

• Integrate with Product Teams: Work closely with product managers, designers, and other engineers to integrate AI capabilities seamlessly into our products, ensuring that features align with user needs and business goals. Youll collaborate cross-functionally to translate product requirements into AI solutions and iterate based on feedback and testing.

• System Evaluation & Iteration: Rigorously evaluate the performance of AI models and pipelines using appropriate metrics including accuracy/correctness, response latency, and avoidance of errors like hallucinations. Conduct thorough testing and use user feedback to drive continuous improvements in model prompts, parameters, and data processing.

• Code Quality & Best Practices: Write clean, maintainable, and testable code while following software engineering best practices. Ensure that the AI components are well-structured, scalable, and fit into our overall system architecture. Implement monitoring and logging for AI services to track performance and reliability in production.

• Mentorship and Knowledge Sharing: Provide technical guidance and mentorship to team members on best practices in generative AI development. Help educate and upskill colleagues (e.g. through code reviews, tech talks) in areas like prompt engineering, using our AI toolchain, and evaluating model outputs. Foster a culture of continuous learning and experimentation with new AI technologies.

Required Skills and Qualifications

• Software Engineering Experience: 3+ years (Mid-level) / 5+ years (Senior) of professional software engineering experience. Rock-solid backend development skills with expertise in Java and designing scalable APIs/services. Experience building and deploying systems on AWS or similar cloud platforms is required (including familiarity with cloud infrastructure and distributed computing). Strong system design abilities with a track record of designing robust, maintainable architectures is a must.

• LLM/AI Application Experience: Proven experience building applications that leverage large language models or generative AI. You have spent time prompting and integrating language models into real products (e.g. building chatbots, semantic search, AI assistants) and understand their behavior and failure modes.

• Cloud & DevOps: Own the product ionization of LLM/RAG-backed services as high-availability, low-latency backends. Expertise in AWS (e.g., ECS/EKS/Lambda, API Gateway/ALB, S3, DynamoDB/Postgres, OpenSearch, SQS/SNS/Step Functions, Secrets Manager/KMS, VPC) and infrastructure-as-code (Terraform/CDK).

• Product and Domain Experience: Experience building enterprise (B2B SaaS) products is a strong plus . This means you understand considerations like user experience, scalability, security, and compliance. Past exposure to these types of products will help you design AI solutions that cater to a range of end-users.

• Strong Communication & Collaboration: Excellent interpersonal and communication skills, with an ability to explain complex AI concepts to non-technical stakeholders and create clarity from ambiguity. You work effectively in cross-functional teams and can coordinate with product, design, and ops teams to drive projects forward.

• Problem-Solving & Autonomy: Self-motivated and able to manage multiple priorities in a fast-paced environment. You have a demonstrated ability to troubleshoot complex systems, debug issues across the stack, and quickly prototype solutions. A "figure it out" attitude and creative approach to overcoming technical challenges are key.

Preferred (Bonus) Qualifications

• Full-Stack & Frontend Skills: While this is primarily a backend/AI role, having a deep full-stack background (especially modern frontend frameworks - Angular) is beneficial. It will help you collaborate with front-end teams and build end-to-end solutions.

• Startup/Agile Environment: Prior experience in an early-stage startup or similarly fast-paced environment where you've worn multiple hats and adapted to rapid changes.