Role: Lead Engineer, AI SaaS Platform We are seeking a seasoned, hands-on Lead Engineer to manage the technical direction and execution of our core AI SaaS platform. This is a crucial role that demands a strong background in modern cloud architecture and AI/ML deployment, as well as excellent leadership skills to mentor and technically steer a high-performing engineering team. You will be the technical anchor for the team, responsible for architecture, code quality, deployment efficiency, and the overall technical health of the application, while also serving as a key motivator and mentor for your colleagues. Key Responsibilities Technical Ownership & Design: Serve as the primary owner for the technical design and implementation of new features. Define and enforce high-quality coding standards and best practices across the team. Hands-On Development (70%+): Actively write, debug, and review complex code across the stack. Tackle challenging technical tasks and lead by example through significant code contributions. Team Guidance & Mentorship: Provide day-to-day technical leadership and mentorship to engineers. Conduct thorough code reviews and help the team efficiently unblock technical challenges. Architecture & Infrastructure: Oversee the integrity of the AWS cloud infrastructure to ensure platform scalability and reliability. Drive automated deployment processes using Terraform (IaC). LLM Integration: Ensure effective, high-performance integration of Large Language Models (LLMs) into the document research workflow. Cross-Functional Collaboration: Partner with the Product Manager to break down requirements, estimate work, and plan execution sprints using Agile methodologies. Required Qualifications Minimum 10 years of industry experience in software development, with significant time spent in a senior or lead technical capacity building a SaaS product. Expert-level proficiency with cloud infrastructure, specifically AWS, and Infrastructure-as-Code tools like Terraform. Strong background in the architecture and deployment of AI/ML applications, particularly those leveraging Large Language Models (LLMs) and Retrieval-Augmented Generation techniques. Experience fine-tuning foundation models and developing deep research systems against a domain knowledge base is desirable. Proven hands-on expertise with our core technology stack. Do not apply if you have not extensively used these tools: Backend: NestJS, Prisma, Node.js Frontend: React, TanStack, Tailwind Database: PostgreSQL, Prisma, Vector search IaC: Terraform, Terragrunt AI/ML: AWS Bedrock, LangChain, RAG, Deep Serch, Agentic AI Python: Lambda, ETL, Document processing Security: Cognito, JWT, RBAC DevOps: Docker, CI/CD, Monitoring Leadership Skills Effective Technical Communication: Ability to clearly document designs, communicate trade-offs, and present solutions to both technical peers and product stakeholders. Mentorship: A passion for guiding and growing junior and mid-level engineers through code reviews, pairing, and knowledge sharing. Proactive Problem-Solving: A high degree of ownership and a relentless drive to identify system weaknesses and implement durable solutions. Team Motivation: Ability to inspire a team, foster a collaborative environment, and maintain high morale and velocity.
Role: Data & AI Engineer We are seeking a talented and detail-oriented Data & AI Engineer to develop and deploy cutting-edge artificial intelligence solutions focused on regulatory compliance. You will play a critical role in leveraging Large Language Models (LLMs) and AWS Bedrock to transform how we manage and interpret critical regulatory data. You should possess excellent communication and collaboration skills, working in a fast-paced agile development environment. Key Responsibilities AI Solution Development: Design, develop, and deploy AI solutions, specifically utilizing AWS Bedrock and other LLMs, to achieve regulatory compliance and enhance data insights. Data Preparation & Embedding: Develop advanced parsing and chunking strategies to handle diverse data sources (Files, APIs, Newsletters, Email Lists, Web pages). Implement processes to embed documents into vector databases efficiently. Vector Database Management: Manage and maintain vector databases, including adding and utilizing custom metadata to optimize retrieval and relevance. RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) systems, focusing on continuous prompt engineering and experimentation to maximize output quality and accuracy. System Integration: Integrate AI/ML studios and various LLM APIs into our core platform infrastructure and software development workflow. MLOps and Optimization: Monitor and continuously optimize RAG model performance. Manage and experiment with MLOps workflows using Amazon SageMaker. Data Storage & Governance: Design and implement robust data storage solutions for sensitive regulatory data, ensuring data integrity, security, availability, and scalability. Required Skills and Qualifications Minimum 5 years of industry experience in software development, with significant time spent in cloud infrastructure and DevOps areas. AI/LLM Expertise: Proven experience developing and deploying solutions using Large Language Models (LLMs) and platforms like AWS Bedrock. RAG Proficiency: Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) systems. Programming Languages: Strong proficiency in Python is essential. Experience with JS and data processing using PySpark is highly desirable. Vector Databases: Direct experience with administering and utilizing Vector Databases such as Qdrant or OpenSearch. Data Management: Expertise in SQL for data querying and management. Tools : Familiarity with Jupyter Notebooks for development and experimentation. MLOps: Experience with MLOps tools and methodologies. AI Development Studios: Experience using the latest AI-assisted software development IDEs like Cursor, GitHub Copilot, etc.
Role: Lead Engineer, AI SaaS Platform We are seeking a seasoned, hands-on Lead Engineer to manage the technical direction and execution of our core AI SaaS platform. This is a crucial role that demands a strong background in modern cloud architecture and AI/ML deployment, as well as excellent leadership skills to mentor and technically steer a high-performing engineering team. You will be the technical anchor for the team, responsible for architecture, code quality, deployment efficiency, and the overall technical health of the application, while also serving as a key motivator and mentor for your colleagues. Key Responsibilities Technical Ownership & Design: Serve as the primary owner for the technical design and implementation of new features. Define and enforce high-quality coding standards and best practices across the team. Hands-On Development (70%+): Actively write, debug, and review complex code across the stack. Tackle challenging technical tasks and lead by example through significant code contributions. Team Guidance & Mentorship: Provide day-to-day technical leadership and mentorship to engineers. Conduct thorough code reviews and help the team efficiently unblock technical challenges. Architecture & Infrastructure: Oversee the integrity of the AWS cloud infrastructure to ensure platform scalability and reliability. Drive automated deployment processes using Terraform (IaC). LLM Integration: Ensure effective, high-performance integration of Large Language Models (LLMs) into the document research workflow. Cross-Functional Collaboration: Partner with the Product Manager to break down requirements, estimate work, and plan execution sprints using Agile methodologies. Required Qualifications Minimum 10 years of industry experience in software development, with significant time spent in a senior or lead technical capacity building a SaaS product. Expert-level proficiency with cloud infrastructure, specifically AWS, and Infrastructure-as-Code tools like Terraform. Strong background in the architecture and deployment of AI/ML applications, particularly those leveraging Large Language Models (LLMs) and Retrieval-Augmented Generation techniques. Experience fine-tuning foundation models and developing deep research systems against a domain knowledge base is desirable. Proven hands-on expertise with our core technology stack. Do not apply if you have not extensively used these tools: Backend: NestJS, Prisma, Node.js Frontend: React, TanStack, Tailwind Database: PostgreSQL, Prisma, Vector search IaC: Terraform, Terragrunt AI/ML: AWS Bedrock, LangChain, RAG, Deep Serch, Agentic AI Python: Lambda, ETL, Document processing Security: Cognito, JWT, RBAC DevOps: Docker, CI/CD, Monitoring Leadership Skills Effective Technical Communication: Ability to clearly document designs, communicate trade-offs, and present solutions to both technical peers and product stakeholders. Mentorship: A passion for guiding and growing junior and mid-level engineers through code reviews, pairing, and knowledge sharing. Proactive Problem-Solving: A high degree of ownership and a relentless drive to identify system weaknesses and implement durable solutions. Team Motivation: Ability to inspire a team, foster a collaborative environment, and maintain high morale and velocity.