Jobs at Blend360

Lead HR for Blend's Mexico office: own full employee lifecycle, build HR processes and compliance, advise leaders on talent strategy, run onboarding, benefits, payroll coordination, HRIS and reporting, manage employee relations, culture, and leadership development.

The Full Stack Sr. Analyst will design, develop, and maintain web applications using React for frontend and Python for backend, collaborating with teams to optimize performance and user experience.

The Full Stack Sr. Analyst will design, develop, and maintain web applications, collaborating with teams and utilizing technologies like React and Python with AWS for scalable solutions.

The Full Stack Sr. Analyst will design, develop, and maintain web applications using React and Python, while collaborating with cross-functional teams and utilizing AWS services for cloud solutions.

Analyze and validate an existing data ecosystem by reviewing SQL, stored procedures, ETL jobs, and data transformations; trace data flows; verify business rules; document implementations, table relationships, and dependencies; and collaborate with technical and business stakeholders to confirm findings.

Validate and document an existing data ecosystem by analyzing SQL code, stored procedures, ETL jobs, and data transformations. Trace data flows, confirm business rule implementations, document table relationships and dependencies, and collaborate with technical and business stakeholders to verify technical findings.

Analyze and validate an existing data ecosystem by reviewing SQL code, stored procedures, ETL jobs, and transformations. Trace data flows, confirm business rule implementations, document data flows, table relationships, and technical dependencies, and collaborate with stakeholders to validate findings.

Analyze and validate an existing data ecosystem by reviewing SQL code, stored procedures, ETL jobs, and data transformations. Trace data flows, confirm business rule implementations, document data flows and dependencies, and collaborate with technical and business stakeholders to validate findings and support discovery.

Validate and document an existing enterprise data ecosystem by analyzing SQL, stored procedures, ETL jobs, and data transformations; trace data flows, confirm business-rule implementation, and collaborate with stakeholders to produce accurate technical documentation.

Lead end-to-end delivery of production AI systems (RAG, agentic frameworks, LLMs), design evaluation and MLOps/LLMOps pipelines, build scalable inference and CI/CD, mentor engineers, and communicate with stakeholders to balance reliability, cost, latency, and business value.

Architect, build, and deploy autonomous AI agents and workflows to support demand generation, lead research, campaign management, and CRM enrichment. Integrate agents with MarTech (HubSpot, Salesforce, 6sense), design prompt engineering and RAG-based systems, implement human-in-the-loop evaluation, and optimize campaign performance while partnering with cross-functional teams to automate the customer acquisition funnel.

Lead end-to-end delivery of production AI systems (RAG, agentic frameworks, LLM solutions), design evaluation and MLOps/LLMOps pipelines, build scalable inference and CI/CD, run structured experiments, identify model failures, design APIs/microservices, and mentor engineers while communicating with stakeholders and clients.

Lead end-to-end delivery of production AI systems (RAG, agentic frameworks, LLM solutions), design evaluation and MLOps/LLMOps pipelines, build scalable inference and CI/CD, run structured experiments, identify model failures, design APIs/microservices, and mentor engineers while advising stakeholders.

Lead end-to-end delivery of production AI systems (RAG, agentic frameworks, LLM solutions). Design evaluation frameworks, run structured experiments, build scalable inference and CI/CD, automate MLOps/LLMOps, design APIs/microservices, mentor engineers, and advise stakeholders on pragmatic AI decisions.

Design, build, and deploy autonomous AI agents and workflows for marketing and sales: research and enrich leads, manage campaigns, personalize nurture with NLP/LLMs, integrate with CRM/MarTech, implement RAG and human-in-the-loop evaluation, and optimize agent performance for ROI.

Design, build, and deploy autonomous AI agents and workflows to support demand generation, lead research, campaign management, and CRM enrichment. Integrate agents with marketing platforms, implement RAG and prompt-engineering strategies, create human-in-the-loop evaluation, and optimize AI-driven campaigns for ROI while partnering with cross-functional teams.

Architect, build, and deploy autonomous AI agents and NLP/LLM workflows to automate lead qualification, CRM enrichment, campaign management, and prospect engagement. Integrate agents with MarTech (HubSpot, Salesforce, 6sense, Google Analytics), implement RAG and prompt-engineering strategies, and create human-in-the-loop evaluation to ensure quality, brand alignment, and ROI optimization.

No responsibilities or qualifications are provided. Title indicates an AI Engineer role associated with a "Mexico Bench" (likely a location-specific bench or candidate pool).

Build and operationalize production-grade agentic LLM systems for marketing analytics: design multi-step agents, RAG pipelines, evaluation frameworks, LLMOps/MLOps (CI/CD, containerization), integrate Claude/OpenAI APIs, implement guardrails and monitoring, write production Python/SQL, and collaborate on deployment and documentation.

Lead discovery and prioritisation of AI opportunities, translate them into value cases and roadmaps, and drive solutions from validation through deployment. Mobilise cross-functional teams, assess technical feasibility and data readiness, establish governance for responsible AI and delivery, and present recommendations to executive stakeholders to realise measurable business outcomes.