Role Description Are you a technically deep developer with a passion for building real solutions, integrating complex systems, and working at the intersection of automation and AI? Do you thrive in fast-moving environments where your code directly impacts how an entire organization operates? We're looking for an AI Automation Engineer to join our internal team in Florida — someone ready to build, integrate, and scale intelligent solutions across departments. For this Full Time position you should be available to work on Eastern Standard Time (EST). Apply Now! In this case, we are looking for someone to join our internal team and provide excellence to make the magic happen. Qualifications - Strong experience with Python. - Experience building and integrating REST APIs and JSON-based services. - Proficiency with Git / version control workflows. - Excellent English written and verbal communication skills. - Solid understanding of LLM fundamentals (prompting, tool usage, function calling). - Ability to perform requirements gathering with non-technical stakeholders. - Strong problem-solving skills and structured thinking. - Experience with .NET / C# and TypeScript (reading, writing, refactoring). - Understanding of web fundamentals (HTML/CSS, HTTP, browser APIs). Requirements - Experience or interest in Microsoft 365 Agents SDK. - Familiarity with Microsoft 365 Agents SDK or Bot Framework. - Experience with Azure / Entra ID / OAuth 2.0. - Knowledge of YAML / configuration-driven systems. - Previous work on a chatbot project. - Experience building integrations for Teams / Slack bots. - Familiarity with RAG / vector databases. - Experience with LiteLLM or multi-model routing. - Knowledge of workflow automation tools. - Experience with ticketing systems. - Familiarity with ERP systems. - Domain knowledge in HR / Finance / PM / IT operations. - Exposure to Databases / SQL / data engineering concepts. - Background in Architecture, Engineering, or Construction (AEC) industries. Benefits - Competitive compensation. - Flexibility. - Constant learning and growth. - Opportunity to work anywhere you want with one of our +130 active clients across the United States. Company Description BetterPros unlocks human potential by offering competitive compensation, flexibility, constant learning and growth, and the opportunity to work anywhere you want with one of our +130 active clients across the United States.

• Design and implement training data generation pipelines, including synthetic data generation. • Build data labeling and annotation workflows with quality validation loops. • Convert enterprise data into formats suitable for model training (instruction-tuning pairs, embeddings). • Implement active learning strategies to identify high-value training examples. • Collaborate with domain experts to validate training data quality and relevance. • Build automated data quality checks: coverage, balance, consistency. • Design training data versioning and lineage tracking. • Analyze model evaluation results to identify training data gaps.

• Rethink the PM job when most users are agents. • Talk to customers across the full spectrum. • Own the problem statement and requirements behind every agent tooling bet. • Decide what gets built, what gets deferred, and what gets cut. • Define how each launch is measured before it ships. • Keep engineering, design, and leadership aligned.

• Manage and evolve the end-to-end architectural blueprint for cloud-native applications at scale — covering compute, data, networking, security, and observability layers on AWS. • Define and promote agentic AI architecture patterns, including multi-agent systems, tool orchestration, memory and retrieval strategies, LLM routing, guardrails, and feedback loops. • Translate these patterns into relevant standards and reusable reference architectures. • Establish and govern DevOps standards across the organization: CI/CD pipeline design, GitOps practices, deployment strategies (blue/green, canary, progressive delivery), environment parity, and release engineering. • Design and oversee platform infrastructure. This includes ECS, Kubernetes clusters (EKS), service mesh, API gateway strategy, secrets management, IAM/RBAC governance, and data stores like DynamoDB, Aurora RDS, Postgres, Elastic/OpenSearch. Additionally, it involves multi-account/multi-region AWS topology. • Lead architecture reviews and provide binding technical decisions on high-risk changes — balancing velocity, reliability, cost, and security. • Define SLOs/SLIs/error budgets, logging standards, distributed tracing, capacity planning, and incident response frameworks. • Introduce new technologies through structured PoC and risk assessment processes; build internal communities of practice around architectural patterns. • Produce architecture decision records (ADRs), system context diagrams, threat models, and runbooks that serve as the source of truth for platform design. • Be a technical advisor to Product and Partners — translating architectural constraints and capabilities into clear strategic options. • Mentor staff and senior engineers on architectural thinking, systems design, and engineering leadership; conduct design reviews that raise the technical bar across teams.