Role Description Estamos em busca de um Tech Lead para liderar tecnicamente nossos times de engenharia, atuando como referência em decisões de arquitetura e desenvolvimento de software. O profissional será responsável por orientar a evolução técnica dos produtos, garantir a qualidade das entregas e promover o crescimento do time, equilibrando visão estratégica com execução hands-on. Procuramos um profissional sênior que combine excelência técnica com habilidades de liderança técnica. Alguém que goste de resolver problemas complexos, tenha prazer em mentorar desenvolvedores e saiba traduzir necessidades de negócio em soluções técnicas sustentáveis. Valorizamos pessoas curiosas, comunicativas e que defendam boas práticas sem perder o pragmatismo necessário para entregar valor continuamente. Responsibilities - Liderar tecnicamente squads de desenvolvimento, definindo padrões, ferramentas e processos. - Projetar arquiteturas escaláveis, resilientes e de fácil manutenção, considerando trade-offs entre performance, custo e complexidade. - Conduzir revisões de código, design reviews e discussões técnicas, elevando o nível técnico do time. - Colaborar com Product Managers, stakeholders e outros times para alinhar roadmap técnico com objetivos de negócio. - Identificar e endereçar dívidas técnicas, propondo planos de refatoração e modernização quando necessário. - Apoiar processos de contratação, onboarding e desenvolvimento de carreira dos membros do time. - Manter-se atualizado sobre tendências tecnológicas e avaliar sua aplicabilidade ao contexto da empresa. Qualifications - Experiência sólida (geralmente 7+ anos) em desenvolvimento de software, com pelo menos 2 anos em posição de liderança técnica. - Domínio profundo de pelo menos uma linguagem de programação moderna (Java, C#, Go, Python, TypeScript ou similar) e familiaridade com múltiplos paradigmas. - Conhecimento aprofundado de padrões arquiteturais como microsserviços, arquitetura hexagonal, event-driven, CQRS, DDD e monólitos modulares, sabendo quando aplicar cada um. - Experiência com design de APIs REST e integração entre sistemas. - Vivência em ambientes cloud (AWS, GCP ou Azure), containers (Docker, Kubernetes) e práticas de DevOps/SRE. - Domínio de bancos de dados relacionais e NoSQL, incluindo modelagem, performance tuning e estratégias de escala. - Prática consolidada em testes automatizados, CI/CD, observabilidade e segurança de aplicações. - Familiaridade com ferramentas de produtividade assistidas por IA no fluxo de desenvolvimento (Claude Code, GitHub Copilot, Cursor). - Experiência prática integrando LLMs em produtos (OpenAI, Anthropic, Google ou modelos open source via Hugging Face, Ollama, etc.). - Domínio de técnicas de prompt engineering, structured outputs e function calling/tool use. - Conhecimento de padrões arquiteturais para aplicações com IA: RAG (Retrieval-Augmented Generation), agentes, pipelines de inferência e orquestração de múltiplos modelos. - Experiência em arquitetura de sistemas de IA em produção, considerando latência, custo por token, fallbacks e degradação graciosa. Requirements - Experiência com design de APIs GraphQL e gRPC. - Vivência com mensageria e arquiteturas assíncronas (Kafka, RabbitMQ, SQS ou similares). - Experiência com bancos vetoriais (pgvector, Pinecone, Weaviate, Qdrant, Chroma) e estratégias de embedding/chunking. - Vivência com frameworks de orquestração de IA (LangChain, LlamaIndex, Semantic Kernel, Haystack). - Conhecimento de protocolos emergentes como MCP (Model Context Protocol) para integração de ferramentas e agentes. Soft Skills Valued - Comunicação clara para públicos técnicos e não-técnicos. - Capacidade de mediar discussões e construir consenso. - Mentalidade de mentoria e desenvolvimento de pessoas. - Pensamento sistêmico e orientação a resultados. - Capacidade de avaliar criticamente quando IA agrega valor real vs. quando uma solução determinística é mais adequada. - Visão pragmática sobre custo/benefício de modelos proprietários vs. open source. - Atenção a riscos éticos e de privacidade ao desenhar soluções com IA. Benefits - Oportunidades 100% remotas 👨🏻‍💻 - Vale home office 💻 - Feedbacks periódicos 💬 - Programa de indicações 🏅 - Acolhimento psicológico 🙋🏻‍♂️ - Ginástica laboral 🏋️ - Academia de conhecimento 🧠 - Convênio com escola de inglês 🔤 - Reuniões mensais de transparência 🔃 - Happy hour online 🍻 - Kit de boas-vindas 🎁

• Build AI agents, automations, and internal tools for People-focused workflows like recruiting, onboarding, mobility, HR operations, and performance cycles. • Work directly with People team members to understand real processes, repeated judgment, and where automation can create immediate leverage. • Use tools like n8n, Claude Code, Notion AI, and the broader stack to ship production-ready solutions that are built, tested, deployed, measured, and improved. • Lead AI enablement across the company by running Vibe’s internal AI Champions program, identifying 1–2 power users per team, equipping them with a playbook, and measuring their impact. • Train non-technical teams through office hours, internal documentation, brown bags, and hands-on sessions that move them from curiosity to adoption. • Help business partners build confidence with AI by teaching roles like recruiters, office managers, or people operations teammates how to create their first agent in one sitting. • Partner with Engineering on the infrastructure layer, including data access, MCP servers, governance, security, and technical foundations for safe business-team building. • Remove blockers for builders in non-engineering teams by translating People and Operations needs into clear technical requirements. • Ensure the systems you build are secure, scalable, maintainable, and compliant with internal expectations. • Define and enforce clear standards for responsible People AI usage, including data classification, approved tools, internal workflows, and sensitive data handling. • Clarify what data can be used, where it can be used, and what must stay within approved environments. • Partner with People, Legal, Security, and Engineering to build guardrails that support fast adoption while protecting trust, privacy, and compliance. • Own adoption and impact by measuring what matters: adoption, time saved, agents in production, workflow quality, internal user NPS, and team-level productivity gains. • Identify the highest-leverage opportunities across People and adjacent operating teams. • Build and execute a pragmatic roadmap with the CPO (Chief People Officer), continuously improving based on real usage, feedback, and measurable outcomes.

Role Description Make an impact while you learn. The Semester of Service Program offers students a volunteer project-based opportunity to support real Federal missions, gaining hands-on experience and valuable career-ready skills. Students must be enrolled not less than half-time in an accredited trade school, technical or vocational institute, junior college, college, university, or other accredited educational institution. With this project, you'll support an AI Editing & Planning Language based project. Qualifications - Applicants will be considered based on their knowledge, skills or abilities related to project needs. - Specifically, applicants should demonstrate experience in: - Prompt Design - LLM Familiarity - Survey Edit Logic - Analytical Reasoning - Python Requirements - To qualify, you must be enrolled not less than half-time in an accredited trade school, technical or vocational institute, junior college, college, university, or other accredited educational institution. - You also must be in good academic standing as defined by your institution. - Attach a copy of your transcripts to your application package for verification.

Role Description Trinnex, a wholly owned subsidiary of CDM Smith, is seeking a versatile, proactive, and highly collaborative Intermediate AI/ML Developer to join our team. We operate in a fast-paced, rapidly evolving environment where taking initiative and ownership is crucial. In this role, you will not just execute tasks, but actively identify opportunities, anticipate bottlenecks, and drive intelligent solutions across a diverse suite of products and services. Because our team works on a wide array of dynamic initiatives, your focus will adapt depending on the active project or product—ranging from predictive modeling and deep learning to natural language processing and generative AI. Operating in an Agile environment, you will collaborate closely with cross-functional teams, transforming complex algorithms into production-ready code. Key Responsibilities - Model Development & Engineering - Design & Implement: Develop, modify, and improve AI/ML solutions across our product and service offerings, adapting to the unique needs of different projects. - Algorithm to Code: Convert theoretical algorithms into clean, robust, and scalable code that leverages machine learning concepts to interpret large and complex datasets. - Fine-Tuning & Customization: Customize, train, and validate machine learning or predictive models to meet specific end-user and business objectives. - Innovation: Explore, evaluate, and implement cutting-edge techniques and methodologies to enhance product performance and develop new features. - Data Analysis & Performance - Data Exploration: Conduct data mining, statistical analysis, and predictive modeling activities to identify patterns and trends within large datasets. - Testing & Validation: Rigorously test and validate AI model accuracy and reliability to ensure they perform to technical and business specifications. - Agile Collaboration, Delivery & Initiative - Sprint Execution: Active participation in Agile sprint planning, daily stand-ups, backlog grooming, and retrospectives to ensure project assignments are delivered on time with excellent quality. - Proactive Problem Solving: Take initiative to identify system inefficiencies, propose solutions, and actively address technical issues or blockers before they impact delivery. - Communication: Clearly and effectively communicate project status, blockers, and technical insights. - Cross-Functional Teamwork: Collaborate with product managers, data engineers, and software developers to integrate models into production environments and resolve technical issues. - Documentation & Best Practices - Technical Documentation: Create comprehensive documentation, including design patterns, technical specifications, and normalization processes to support data architecture and modeling efforts. - Continuous Learning: Maintain active working and learning relationships with industry innovators and peer groups to keep our practices current. Qualifications - Strong proficiency in modern software development using Python (knowledge of C/C++, Java is a plus). - Practical experience with popular machine learning and deep learning toolkits (e.g., Scikit-Learn, PyTorch, TensorFlow, Hugging Face). - Solid capability in querying and manipulating large datasets using SQL and data processing libraries (e.g., Pandas, NumPy). - Familiarity with cloud platforms (GCP preferred), model deployment practices (MLOps, Docker), and CI/CD pipelines is highly advantageous. - A self-starter mindset with a strong drive to take ownership of tasks, troubleshoot issues independently, and actively contribute ideas to improve products and processes. - Ability to thrive and remain agile in a fast-paced, highly dynamic environment, pivoting comfortably between different product focuses. - Demonstrated experience working effectively within Agile/Scrum methodologies. - Strong communication skills with the ability to bridge the gap between technical details and business outcomes. - Analytical and critical thinking skills with a meticulous approach to model validation and code quality. Requirements - Bachelors’ Degree. - 2 years of relevant experience. - Equivalent additional directly related experience will be considered in lieu of a college degree. - Domestic and/or international travel may be required. The frequency of travel is contingent on specific duties, responsibilities, and the essential functions of the position, which may vary depending on workload and project demands. Background Check and Drug Testing Information CDM Smith Inc. and its divisions and subsidiaries (hereafter collectively referred to as “CDM Smith”) reserves the right to require background checks including criminal, employment, education, licensure, etc. as well as credit and motor vehicle when applicable for certain positions. In addition, CDM Smith may conduct drug testing for designated positions. Background checks are conducted after an offer of employment has been made in the United States. The timing of when background checks will be conducted on candidates for positions outside the United States will vary based on country statutory law but in no case, will the background check precede an interview. CDM Smith will conduct interviews of qualified individuals prior to requesting a criminal background check, and no job application submitted prior to such interview shall inquire into an applicant's criminal history. If this position is subject to a background check for any convictions related to its responsibilities and requirements, employment will be contingent upon successful completion of a background investigation including criminal history. Criminal history will not automatically disqualify a candidate. In addition, during employment individuals may be required by CDM Smith or a CDM Smith client to successfully complete additional background checks, including motor vehicle record as well as drug testing.