Software Engineer - Agentic AI (Lead GenAI & Data Engineer) Location: Charlotte, NC (CIC - 1525 W W.T. Harris Blvd) Hybrid: 3 days/week in office (Monday & Tuesday required). Team primarily based at CIC; Uptown location also acceptable. Employment Type: Contract (12 months; potential extension or conversion) Line of Business: TCOO Number of Openings: 1 Role Overview We are seeking a Lead GenAI & Data Engineer to design, build, and scale intelligent, enterprise-grade Agentic AI systems. In this role, you will work hands-on with Google Agent Development Kit (ADK) and LangChain/LangGraph to create AI agents that integrate deeply with enterprise Systems of Record (SoRs) through reliable, governed data pipelines. You will lead the end-to-end delivery of AI agent solutions-from architecture and workflow design to production deployment-while ensuring performance, observability, security, and compliance. This role requires strong collaboration with business, operations, and process excellence teams to deliver real-world AI copilots and agents with measurable business impact. Key Responsibilities
- Design and develop agentic AI applications using Google ADK, LangChain, and LangGraph, including:
- Multi-agent orchestration
- State and memory management
- Tool integration using enterprise-approved LLMs
- Integrate AI agents with enterprise Systems of Record by building and maintaining secure APIs, connectors, and data pipelines across structured and unstructured data sources.
- Incorporate organization-approved foundation models (e.g., Google Gemini, Anthropic) into task-oriented, agent-based workflows.
- Collaborate with Process Excellence, Operations, and business partners to identify, prototype, and implement AI agents and copilots.
- Build scalable, production-ready Python services supporting agent workflows, including RAG, tool calling, structured outputs, and memory.
- Engineer batch and streaming data pipelines to provide governed, high-quality data access for AI systems.
- Develop and optimize advanced SQL queries for analytics, feature extraction, and real-time agent decisioning.
- Implement observability, evaluation, guardrails, and cost controls across data and AI layers to ensure quality, reliability, compliance, and efficiency.
- Apply cloud-native tools and best practices (GCP preferred; Azure/AWS acceptable) to ensure data quality, lineage, and secure operations.
Minimum Qualifications
- 5+ years of Software Engineering experience, or equivalent demonstrated through a combination of work experience, consulting, education, training, or military experience.
- 5+ years of hands-on experience in GenAI, Agentic AI, and AI/Data Engineering roles.
- Strong proficiency in Python for backend services, AI pipelines, and workflow orchestration.
- Hands-on experience building agentic AI solutions using Google ADK and LangChain/LangGraph.
- Advanced prompt engineering and context engineering skills.
- Solid data engineering background, including:
- Building ETL/ELT pipelines
- Integrating data from APIs, databases, files, and streaming sources
- Managing data quality, schema evolution, and lineage
- Advanced SQL skills (complex joins, window functions, query optimization).
- Experience implementing RAG architectures and integrating LLMs with enterprise data sources (vector stores and relational systems).
- Experience delivering production-grade systems, including testing, CI/CD, logging, monitoring, and error handling.
- Ability to consult on complex, large-scale initiatives, evaluate ambiguous problems, and collaborate strategically with cross-functional stakeholders.
Preferred Qualifications
- Experience with modern data stack tools such as dbt, Airflow/Cloud Composer, Kafka/Pub/Sub, BigQuery, or Snowflake.
- Familiarity with vector databases and hybrid retrieval strategies.
- Experience deploying scalable solutions on Google Cloud Platform (preferred).
- Knowledge of data governance, security, and PII handling within AI and data pipelines.
- Experience with LLMOps practices, including evaluation frameworks, prompt/version management, tracing, and cost optimization.
- Experience implementing AI safety, guardrails, and risk controls in enterprise environments.
Additional Information
- Work Authorization: As applicable per contract requirements
- Supplier Requirements:
- All resumes must be submitted via Beeline to be considered
- No direct outreach or resume solicitation to the hiring manager while the role is open
