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successfactors

AI Software Engineer

Globant
New York, USA
Mid · 3+ years experience
Onsite
Discovered 6 days ago
awsdatabricksdelta-lakeicebergjavakubernetes

Full Job Posting

What You Will Do

  • Design, develop, and troubleshoot agent components, including orchestration logic, tools, and task queues supporting research, summarization, and follow-up workflows. Build and maintain Model Context Protocol (MCP) servers that provide secure access to CRM systems, client and product reference data, document stores, calendars, and email, enforcing user entitlements on every call. Write secure, high-quality production code in Python, and review, debug, and improve code written by others. Develop retrieval pipelines for product, pricing, legal, and client documents, including ingestion, chunking, embedding, indexing, and citation metadata to ensure answers are traceable to their sources. Build data pipelines and feature engineering jobs on Databricks to prepare CRM, transaction, and engagement data for model training and copilot retrieval. Contribute to MLOps workflows for propensity, next-best-action, and opportunity-scoring models, including training jobs, automated testing, and promotion of model artifacts from development through user acceptance testing (UAT) to production. Develop the copilot’s user-facing experience and streaming interactions using AG-UI, including human-in-the-loop review before communications are sent to clients or changes are written to CRM. Create agent evaluations, including offline test sets, groundedness and citation checks, CI/CD regression suites, and LLM-as-judge scoring. Instrument services with OpenTelemetry tracing to support observability and troubleshooting. Use enterprise-authorized AI-assisted development tools while validating generated outputs for correctness, performance, and security. Identify opportunities to eliminate recurring issues or automate remediation to improve the operational stability of agents and model services. Contribute to a team culture rooted in diversity, opportunity, inclusion, and respect.

What You Bring

  • Formal training or certification in software engineering concepts and at least 3 years of applied experience. Hands-on experience in system design, application development, testing, and operational stability. Proficiency in Python and at least one additional language, such as Java, TypeScript, or SQL. Experience building and consuming APIs and event-driven services in a cloud environment. Experience with data processing frameworks such as Apache Spark and large structured datasets. Working knowledge of LLM application development, including prompting, tool calling, retrieval-augmented generation (RAG), and evaluation. Experience using approved AI-assisted software development tools, with sound judgment when validating their outputs. Understanding of responsible AI practices, data sensitivity, and secure handling of inputs and outputs. Solid understanding of agile delivery practices, CI/CD, application resiliency, and security. Practical cloud-native experience, including containers and Kubernetes; AWS experience is preferred.

Nice to Have

  • Experience with agent frameworks such as Google ADK or LangGraph and protocols such as MCP, A2A, or AG-UI. Experience with vector search and retrieval systems such as OpenSearch, pgvector, or FAISS, including reranking and document parsing. Experience with Databricks, MLflow, and Delta Lake or Apache Iceberg. Exposure to model serving on Kubernetes and monitoring for drift, latency, and accuracy. Familiarity with Salesforce or other CRM platforms, including their APIs and data models. Front-end development experience with TypeScript and React for conversational or assistant interfaces. Exposure to payments, treasury services, commercial cards, or sales enablement processes. Familiarity with Terraform and infrastructure as code. Ready to Make an Impact? Join Globant and help build secure, reliable AI-powered experiences that connect enterprise data with meaningful business workflows.
  • Formal training or certification in software engineering concepts and at least 3 years of applied experience. Hands-on experience in system design, application development, testing, and operational stability. Proficiency in Python and at least one additional language, such as Java, TypeScript, or SQL. Experience building and consuming APIs and event-driven services in a cloud environment. Experience with data processing frameworks such as Apache Spark and large structured datasets. Working knowledge of LLM application development, including prompting, tool calling, retrieval-augmented generation (RAG), and evaluation. Experience using approved AI-assisted software development tools, with sound judgment when validating their outputs. Understanding of responsible AI practices, data sensitivity, and secure handling of inputs and outputs. Solid understanding of agile delivery practices, CI/CD, application resiliency, and security. Practical cloud-native experience, including containers and Kubernetes; AWS experience is preferred.

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