Technical Lead - Forward Deployment Engineer AI in Charlotte

Energy Jobline ZR; Charlotte (NC); On-site; USD 140,000 - 210,000; Full time

Job summary

Energy Jobline ZR in Charlotte, NC seeks a Forward Deployment Engineer (FDE) Technical Lead to drive AI-enabled solutions and production deployments. You will lead the technical approach, prototype rapidly, and own customer outcomes.

The role requires hands-on coding, cloud experience, and the ability to guide engineers across software, AI and data platforms while communicating decisions clearly to stakeholders.

Qualifications

• Bachelor's or master's degree in computer science or a related field.
• Strong programming skills in Python, Java/JavaScript, C++ or equivalent.
• Experience developing backend services, APIs, and distributed applications.
• Hands-on exposure to Large Models and Generative AI application development.

Responsibilities

• Lead technical discovery sessions to understand customer problems and data landscape.
• Own the end-to-end technical implementation from discovery to production deployment.
• Design and develop application services, APIs, integrations and AI-enabled solutions.
• Remain hands-on with coding, debugging and code reviews.
• Guide engineers across software, AI, data, cloud and platform technologies.

Skills

Python

Java/JavaScript

C++

Cloud platforms

Education

Bachelor's or master's degree in computer science or related field

Tools

Git

CI/CD

Job description

Role: Forward Deployment Engineer (FDE) Technical Lead - Artificial Intelligence

Location Options: Santa Clara, CA / Atlanta, GA / Cincinnati, OH / Edison, NJ / Miami, FL / Charlotte, NC / Houston, TX

Job Description

The Forward Deployment Engineer (FDE) Technical Lead is a hands-on engineering leader responsible for solving complex problems by combining software engineering, AI/GenAI, data, cloud, integration and platform technologies.

The Technical Lead works directly with customer stakeholders, architects and engineering teams to understand business problems, define the technical approach, rapidly develop prototypes, and lead solutions through engineering integration and production deployment.

Unlike a traditional development lead, the FDE Technical Lead is expected to operate effectively in ambiguous environments, make pragmatic technical decisions, write and review code, troubleshoot complex issues, and take end-to-end ownership of customer outcomes.

Key Responsibilities

• Lead technical discovery sessions to understand customer business problems, existing technology landscape, data, applications and constraints.
• Translate customer requirements and business problems into scalable technical solutions.
• Own the end-to-end technical implementation from discovery and prototyping through production deployment.
• Design and develop application services, APIs, integrations and AI-enabled solutions.
• Remain hands-on with coding, debugging, code reviews and technical troubleshooting.
• Lead rapid prototyping and Proof-of-Concept development to validate solution approaches.
• Define application architecture, APIs, data flows, integration patterns and deployment approaches.
• Guide engineers across software, AI, data, cloud and platform technologies.
• Review code and ensure engineering quality, security, scalability and maintainability.
• Diagnose complex application, data, integration, infrastructure and production issues.
• Drive solutions from prototype to production-ready implementation.
• Mentor junior and graduate FDEs and provide technical support and guidance.
• Communicate technical decisions, trade-offs, risks and recommendations clearly to customer stakeholders.

Qualifications

• Bachelor's or master's degree in computer science or related field.
• Strong programming skills in Python, Java/JavaScript, C++ or equivalent.
• Experience developing backend services, APIs, and distributed applications.
• Experience processing and transforming structured and /or unstructured data.
• Hands-on experience with at least one major cloud platforms: AWS, Microsoft Azure, or Google Cloud.
• Experience in Git, testing frameworks, code reviews and modern software engineering practices.
• Strong debugging and troubleshooting capabilities.
• Hands-on exposure to:
  • Large Models and Generative AI application development.
  • LLM APIs and model integration.
  • Prompt engineering and structured outputs.
  • RAG architectures.
  • Embeddings and vector search/vector databases.
  • Understanding of AI application performance, security and cost considerations.
  • Integration of AI capabilities into enterprise applications.
• Understanding of production monitoring, logging and observability.

Good to Have

• Experience delivering solutions in customer-facing environments.
• Experience leading small Agile engineering teams.
• Hands-on experience with enterprise GenAI implementations.
• Experience with vector databases such as pgvector, Pinecone, Weaviate, Milivus or similar technologies.
• Experience with frameworks for building AI applications and agents.
• Cloud and/or AI certifications.

EOE

Our client is an Equal Opportunity Employer, committed to a workplace free from discrimination and harassment. Employment decisions are based on business needs, job requirements, and individual qualifications without regard to , , , , , , , , marital status, military service, genetic information, or any other status protected by law.