Full Stack Engineer

Mindlance is seeking a Senior Full Stack Engineer to design and develop high-quality software solutions. The role involves collaborating with stakeholders, maintaining engineering standards, and leading Agile practices while focusing on Generative AI applications.

Responsibilities:

• Design and deliver high-quality software that is scalable, secure, and reusable—leveraging modern technologies, proven design patterns, and cloud-native practices to power BigFuture’s core tools
• Design and implement solutions using the latest technologies, deep familiarity with AWS serverless stacks, Dynamo DB, React and Node JS
• Collaborate with product owners, architects, and stakeholders to uphold the highest engineering standards and translate big ideas into impactful, student-facing solutions
• Break down new product capabilities into actionable, verifiable technical changes that move quickly from concept to reality
• Create sharable documentation, both technical and non-technical
• Maintain clean code and strong engineering standards such that when prototypes are greenlit for further development, the project is easy to build upon
• Continuously develop the skills required to work with this rapidly developing technology
• Participate in, or lead Agile SCRUM ceremonies (Sprint Planning, Grooming, Daily SCRUM, Demo) by contributing to team deliverables and driving alignment, focus, and momentum across sprints
• Elevate team performance by giving and receiving thoughtful code reviews, mentoring peers, and helping solve complex technical challenges
• Assist in resolving production issues with urgency and precision, ensuring a smooth and reliable user experience
• Model discipline in adhering to development standards, security practices, and CI/CD principles while helping the team move fast without compromising quality
• Continuously grow your skills and embrace a poly-skilled environment where everyone contributes beyond their specialty
• Serve as an organizational Subject Matter Expert on implementing Generative AI applications
• Work with our Enterprise Architecture team to review and/or establish implementation patterns involving Generative AI tools
• Advise on, and where feasible, create tools and infrastructure that will enable teams to safely deploy Generative AI tools
• Keep abreast of developments in GenAI capabilities and implementations
• Share knowledge of new developments with the team via chats, meetings, and presentations when appropriate
• Serve as an advisor to internal teams developing staff education around Generative AI

Requirements:

• Strong knowledge and hands-on experience with back-end technologies such as Node.js and/or Python
• Experience with asynchronous programming and event-driven messaging patterns
• Strong knowledge of AWS services (e.g., Lambda, SNS, SQS, S3, Step Functions, IAM, KMS, API Gateway, CloudWatch, DynamoDB)
• 5+ years' experience with relational and NoSQL databases (e.g., DynamoDB, OpenSearch, ElasticSearch, PostgreSQL, MySQL, Redshift)
• 5+ years of Software engineering experience designing, building, testing, and managing scalable web applications in AWS cloud-hosted environments
• 1+ years working with LLMs, NLP, or applied ML systems
• Proficiency in reviewing and improving code structure and architecture for testability, maintainability, and scalability, with hands-on experience in JavaScript/TypeScript, React, Node.js, Next.js, APIs, and AWS Serverless technologies (Lambdas, DynamoDB, S3, CloudWatch, etc.)
• Enthusiasm for learning new technologies, especially in the fast-moving GenAI space
• Hands-on experience with LLM frameworks and APIs (e.g., OpenAI, Anthropic)
• Familiarity with prompt engineering, few-shot learning, and context management techniques
• Experience working in Agile/Scrum environments
• Strong analytical thinking, structured problem-solving, and practical decision-making skills
• Effective communication and documentation skills
• Strong problem-solving skills, working collaboratively with team members to identify and resolve issues, and partnering with Product Owners to prioritize backlog
• Proven ability to pitch new ideas and implement improved systems and processes, delivering excellent results
• Effective communicator and able to provide actionable feedback, mentor team members, and participate in interviews to evaluate engineering talent
• Bachelor's degree in computer science, Machine Learning, or related engineering fields