About the role This is not a role where you will bolt AI onto an existing product as an afterthought. SqlDBM is rebuilding core workflows around AI — from how data architects design schemas to how engineers validate changes to how governance teams maintain compliance across enterprise environments. You will work at the intersection of .NET backend engineering and applied AI — building the systems that make AI a first-class, reliable, enterprise-grade capability inside one of the most technically demanding categories in data infrastructure. This role sits inside our dedicated AI group and reports directly to senior leadership. You will have a short line to product, architecture, and business decisions — no layers, no queue. The team is small by design, moves fast, and has direct visibility into enterprise customer needs. What makes this role different You are not building a chatbot. You are building AI infrastructure for enterprise data teams — systems that understand schema context, generate governed artifacts, and integrate into the workflows of the world's most sophisticated engineering organizations. The problems are hard. The customers are demanding. The work is meaningful. What you'll do You will own and extend the backend systems that power SqlDBM's AI capabilities. Specific areas include: - AI-assisted data modeling workflows — backend services that allow users to describe their data needs in natural language and receive accurate, governed schema output - Context-aware intelligence — systems that use the full richness of a user's data model, naming standards, and governance rules to produce AI output that is specific to their environment, not generic - Automated documentation and metadata generation — AI pipelines that analyze existing schemas and produce accurate, consistent business documentation at scale - Integration with enterprise AI ecosystems — API layers that allow external AI agents and tools to call SqlDBM as a trusted source of schema context - Consumption tracking and orchestration — backend infrastructure that manages AI request routing, model selection, cost optimization, and usage metering - Governance-aware AI workflows — systems that embed approval, validation, and compliance logic into AI-generated outputs before they reach production - MCP server development — building and extending SqlDBM's Model Context Protocol server so that external AI agents and LLM-based tools can use SqlDBM as a trusted, real-time schema authority - Tech Stack includes: C# / .NET AWS PostgreSQL Redis REST APIs LLM Integration MCP Microservices Our backend is built on modern .NET with a microservices architecture deployed on AWS. AI capabilities are built on top of major LLM providers via API, with proprietary prompt engineering, context management, and output validation layers that are core intellectual property of the platform. Qualifications - 5+ years of backend engineering experience with C# and .NET - Strong understanding of REST API design and asynchronous service architectures - Experience integrating with external APIs and managing complex data pipelines - Comfort working with LLMs via API — understanding of prompt construction, context management, token economics, and output validation - Experience building systems that handle variable, structured data — schemas, metadata, or similar - Strong engineering fundamentals — testing, code review, system design, observability - Ability to work independently in a remote-first, fast-moving engineering team Strong Plus - Experience with data modeling, database design, or data engineering tooling - Familiarity with enterprise data platforms — Snowflake, Databricks, dbt, or similar - Background building developer tools or platforms used by technical teams - Experience with agentic AI workflows, tool-use patterns, or AI infrastructure - Knowledge of semantic layer concepts, ontologies, or structured metadata systems - Familiarity with Model Context Protocol (MCP) — building or consuming MCP servers in agentic AI architectures What We Offer - Competitive base salary and equity in a profitable, growing company - Fully remote — work from anywhere - Direct impact on product direction — small team, no layers, your work ships to enterprise customers - Work on genuinely hard technical problems at the frontier of AI and enterprise data infrastructure - Collaborative, engineering-driven culture that moves fast and trusts its people - Benefits - comprehensive insurance coverage for employees and their dependents — including medical, dental, vision, life, and both short- and long-term disability, parental leave, an employer-sponsored 401(k) retirement plan, and stock options. Why now SqlDBM is at an inflection point. We have enterprise customers, a profitable business, and a product that is becoming something significantly more powerful. The engineers who join now will shape what that means and build the systems that define the next chapter of data architecture tooling.

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. WHY JOIN US If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! ABOUT THE ROLE We are looking for a Full Stack AI Software Engineer to build modern applications while shaping how AI enhances the software development lifecycle. In this role, you’ll design scalable systems across Python, Node.js, and React while defining best practices for AI-assisted coding, code analysis, and developer productivity. You’ll play a key role in driving engineering excellence by integrating LLM-powered tools into real-world development workflows. WHAT YOU WILL DO - Design, build, and maintain high-quality fullstack applications using modern technologies; - Write clean, scalable, and maintainable code across both frontend and backend systems; - Define and implement best practices for leveraging AI models to review, analyze, and improve code quality; - Use AI tools to enhance development workflows and engineering productivity; - Evaluate and implement AI-assisted development approaches across the engineering lifecycle; - Collaborate with other engineers to improve development standards, code reviews, and technical architecture; - Take ownership of technical solutions and drive engineering excellence across projects. MUST HAVES - 4+ years of experience in full-stack development with React and .NET / C#; - Proven experience building and shipping production-grade software systems; - Experience using AI tools such as OpenAI, Claude Code, or similar; - Proven experience with Azure; - Ability to define and implement best practices for integrating AI into the software development lifecycle; - Strong coding skills and software engineering fundamentals; - Ability to work independently and take ownership of complex technical initiatives; - Upper-intermediate English level. NICE TO HAVES - Additional experience working with AI/LLM-powered development tools or AI-assisted coding workflows; - Experience designing or integrating AI models or AI-driven development processes; - Background in AI/ML engineering, LLM applications, or AI-based developer tooling. PERKS AND BENEFITS - Professional growth: Mentorship, TechTalks, and personalized growth roadmaps. - Competitive compensation: USD-based pay with education, fitness, and team activity budgets. - Exciting projects: Modern solutions with Fortune 500 and top product companies. - Flextime: Flexible schedule with remote and office options.

AI Sr. Engineer – LLMOps & MLOps - 100% Remote Job Description This is a high-stakes, execution-focused role within the Transformation Office. We are looking for a "day-one" engineer to own the production lifecycle of our AI initiatives. Your mission is to build the automated infrastructure that bridges our legacy data systems with modern AWS and Azure AI services. You will be responsible for the "Ops" of AI: ensuring that LLM applications, RAG pipelines, and traditional ML models are deployable, observable, and scalable in a multi-cloud environment. Key Responsibilities • Multi-Cloud Pipeline Execution: Build and maintain automated CI/CD and CT (Continuous Training) pipelines across AWS (SageMaker/Bedrock) and Azure (AI Studio). • LLMOps Framework Implementation: Design and execute the infrastructure for Retrieval-Augmented Generation (RAG), including vector database management (OpenSearch, Pinecone, or Azure AI Search) and semantic index optimization. • Legacy Data Connectivity: Build the engineering "pipes" to securely ingest and move data from legacy systems (Mainframes, SQL Server, on-prem DBs) into cloud-native MLOps workflows. • Automated Model Evaluation: Implement systemized frameworks for LLM evaluation (LLM-as-a-judge, ROUGE, METEOR) and traditional ML validation to ensure performance before deployment. • Observability & Monitoring: Deploy real-time monitoring for model drift, hallucination detection, latency, and token consumption to manage both quality and cost. • Infrastructure as Code (IaC): Manage all AI resources using Terraform or CloudFormation, ensuring the cloud posture is reproducible, secure, and follows a "Privacy by Design" mandate. • Advanced Analytics Integration: Partner with teams using platforms like Palantir, Databricks, or Snowflake to ensure a high-fidelity data flow between analytical ontologies and production models. • IT & Security Diplomacy: Work directly with central IT and Security to navigate IAM roles, VPC peering, and firewall configurations, clearing the path for rapid transformation. • Scalable Inference Engineering: Optimize model serving endpoints for high-throughput and low-latency, utilizing containerization (Docker/Kubernetes) and serverless architectures where appropriate. • Prompt & Model Versioning: Establish rigorous version control for prompts (PromptOps), model weights, and data snapshots to ensure 100% auditability and rollback capability. • Data Science Engineering: Support the data science lifecycle by automating feature stores, feature engineering pipelines, and the transition of experimental notebooks into hardened production microservices. • Security & Compliance Hardening: Implement automated scanning and guardrails (e.g., Bedrock Guardrails or Azure Content Safety) to prevent prompt injection and data leakage. - Qualifications • Education: Bachelor’s degree in Computer Science or a related field required; Master’s degree in a quantitative discipline highly desirable. • Proven Execution: 6+ years of engineering experience, with a minimum of 3 years strictly focused on MLOps or LLMOps in a production environment. • AWS & Azure Mastery: Deep, hands-on proficiency in both ecosystems. You must be able to configure Bedrock and Azure OpenAI services, including private networking and endpoint security, on day one. • Technical Stack: Expert Python, SQL, and PySpark. Extensive experience with containerization (Docker, Kubernetes) and orchestration tools (Airflow, Kubeflow, or Step Functions). • LLM Tooling: Professional experience with evaluation and observability frameworks like LangSmith, Arize Phoenix, or WhyLabs. • Data Science Flavor: A strong understanding of statistical validation, model evaluation metrics, and the ability to partner with Data Scientists to optimize model performance. • Transformation Mindset: The ability to move at the speed of a startup while maintaining the collaborative relationships required to function within a large-scale enterprise IT landscape.

Banyan Software provides the best permanent home for successful enterprise software companies, their employees, and customers. We are on a mission to acquire, build and grow great enterprise software businesses all over the world that have dominant positions in niche vertical markets. In recent years, Banyan was named the #1 fastest-growing private software company in the US on the Inc. 5000 and amongst the top 10 fastest-growing companies by the Deloitte Technology Fast 500. Founded in 2016 with a permanent capital base setup to preserve the legacy of founders, Banyan focuses on a buy and hold for life strategy for growing software companies that serve specialized vertical markets. AI Engineer (Healthcare SaaS) Location: Remote (must be inside the United States) Reports to: Chief Technology and Product Officer About Medicat (One of Banyan's Portfolio Companies) Medicat is building modern software infrastructure for healthcare organizations through our platform, MedicatOne. Our mission is to simplify complex healthcare operations through intuitive software, strong data infrastructure, and intelligent automation. As we expand our platform capabilities, we are investing in AI-driven features that improve how healthcare organizations interact with their data, workflows, and operational systems. We are seeking an experienced AI Engineer to help design and implement AI-native capabilities within MedicatOne. The Role This is a high-impact individual contributor role. This is a hands-on engineering role focused on building production-grade AI capabilities inside a growing healthcare SaaS platform. You will work closely with product leadership and engineering to architect and deploy AI-powered systems that interact with structured healthcare data and operational workflows. The role requires strong technical execution as well as fluency in data analytics and healthcare informatics concepts. This is a build-and-ship role where you will play a key part in translating AI opportunities into real product functionality. In this position, you will help to accelerate engineering performance and drive AI-enabled innovation across Medicat in our workflows and in our SaaS product. What You’ll Do AI System Development - Design and implement AI-powered capabilities within the MedicatOne platform - Integrate modern AI models and services into production workflows - Develop systems that interact with structured application data and APIs - Ensure AI features are reliable, performant, and secure Data & Informatics - Work with large datasets related to healthcare operations - Design systems that leverage structured data effectively - Build logic that enables intelligent interpretation of operational data - Collaborate with engineering on data pipelines, schemas, and analytics frameworks Platform Integration - Integrate AI capabilities into existing SaaS architecture - Work with backend engineers to ensure scalable system design - Optimize performance of data-intensive AI workflows - Contribute to platform-level architecture decisions Execution & Iteration - Ship production-ready AI features quickly and iteratively - Collaborate closely with leadership on prioritization and implementation - Help establish best practices for AI development within the organization What We’re Looking For Experience - 5+ years building production SaaS systems - Direct experience building and implementing AI/ML or LLM-based features - Strong experience working with structured data and analytics systems - Experience working with healthcare data or healthcare SaaS environments, including familiarity with the regulatory, privacy, and compliance considerations that shape technical decisions (HIPAA, PHI handling, de-identification) - Demonstrated ability to build and deploy systems end-to-end Technical Skills You should be comfortable with: - Working knowledge of modern AI infrastructure and patterns, including: - LLM API integration (OpenAI, Anthropic, or similar) in production environments - Retrieval-Augmented Generation (RAG): designing retrieval pipelines, chunking strategies, and grounding LLM responses in real data - Vector databases: embedding, indexing, and querying unstructured or semi-structured data - Data modeling and SQL - Data pipelines and analytics workflows and working with large structured datasets - API design and backend services - Working with large, structured datasets Experience with healthcare informatics standards or healthcare data environments is strongly preferred. What Success Looks Like - AI capabilities successfully integrated into the MedicatOne platform - Production-ready systems that interact effectively with operational data - High-quality implementations that balance accuracy, performance, and usability - Scalable architecture supporting future AI development Why Join Medicat - Work directly with company leadership on high-impact initiatives - Build meaningful AI capabilities in a real healthcare environment - High ownership and autonomy in a growing SaaS company - Opportunity to shape the future of AI within the platform Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Teams, associates, our Operating Companies, and the communities we serve. Our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance. The expected base salary for this position is: USD $90,000 - $120,000 excluding annual bonus and equity (when applicable). Salary is based on several factors including market conditions, location and may vary depending on job-related skills and experience. Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Global Teams, associates, our Operating Companies, and the communities we serve. As a collective, our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance. Recruitment Notice Banyan Software may use artificial intelligence (AI) tools to assist in screening and/or assessing applicants during the recruitment process. All hiring decisions are made by our team. Personal information submitted through your application will be collected and used for recruitment purposes in accordance with applicable privacy laws. Contact us at any time with questions about our process or to request accommodation. Beware of Recruitment Scams We have been made aware of individuals fraudulently posing as members of our Talent Acquisition team and extending fake job offers. These scams may involve requests for personal information or payment for equipment. Protect yourself by following these steps: - Verify that all communications from our recruiting team come from an @banyansoftware.com email address. - Remember, employers will never request payment or banking information during the hiring process. - If you receive a suspicious message, do not respond — instead, forward it to careers@banyansoftware.com and/or report it to the platform where you received it. Your safety and security are important to us. Thank you for staying vigilant.