Pinecone Vector Databases Jobs in Washington (NOW HIRING)

Job Summary:
GCI Incorporated is a company that embodies excellence, integrity, and professionalism in delivering high-value mission solutions. They are seeking an experienced AI/ML Software Engineer to design, develop, deploy, and maintain advanced artificial intelligence and machine learning solutions in mission-critical environments, focusing on building scalable AI-powered applications and machine learning pipelines.
Responsibilities:
• Design, develop, test, debug, and deploy AI-enabled software applications, machine learning services, and intelligent automation tools.
• Develop and maintain scalable cloud-native and on-prem AI/ML solutions supporting mission-critical operations.
• Build and integrate machine learning models, generative AI capabilities, and LLM-powered applications into production systems.
• Design and implement Retrieval-Augmented Generation (RAG) architectures leveraging vector databases, embeddings, and enterprise knowledge repositories.
• Develop and maintain data ingestion, transformation, feature engineering, and model inference pipelines.
• Collaborate with data scientists, machine learning engineers, analysts, project managers, and subject matter experts to operationalize AI capabilities.
• Deploy AI/ML workloads within AWS-based cloud environments using Infrastructure as Code (IaC) and automated CI/CD pipelines.
• Design and optimize vector search, semantic search, and traditional search solutions using OpenSearch, Elasticsearch, or equivalent technologies.
• Implement model monitoring, observability, performance tuning, and automated retraining workflows.
• Ensure responsible AI practices, including model 'explainability', governance, security, privacy, and compliance requirements.
• Troubleshoot complex production issues involving AI models, data pipelines, cloud services, and distributed systems.
• Maintain technical documentation for AI architectures, model deployment processes, and operational procedures.
• Research and evaluate emerging AI, machine learning, and cloud technologies and provide recommendations for continuous improvement.
• Partner with engineering teams to advance organizational AI capabilities and accelerate adoption of modern AI technologies.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Information Technology, or other related technical discipline, or equivalent combination of education, technical certifications, training, and work/military experience.
• Demonstrated hands-on experience with Python and modern software engineering practices, including Git, automated testing, and code reviews.
• Demonstrated hands-on experience developing and deploying RESTful APIs and microservices.
• Demonstrated experience building, integrating, and deploying machine learning models in production environments.
• Demonstrated experience with generative AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent technologies.
• Demonstrated experience working with Large Language Models (LLMs), prompt engineering, model evaluation, and retrieval-augmented generation (RAG) architectures.
• Demonstrated hands-on experience with vector databases and semantic search technologies, including OpenSearch, Elasticsearch, Pinecone, Weaviate, Chroma, or equivalent platforms.
• Demonstrated hands-on experience with AWS cloud services and AI/ML offerings, including S3, EC2, IAM, VPC, SageMaker, Bedrock, Lambda, and related services.
• Demonstrated experience applying object-oriented design principles and software architecture patterns to build scalable, maintainable, and secure production systems.
• Demonstrated experience designing and implementing data pipelines supporting machine learning training and inference workloads.
• Understanding of MLOps principles, including model versioning, deployment automation, monitoring, and lifecycle management.
• A candidate must be a US Citizen and requires an active/current TS/SCI with Polygraph clearance.
Preferred:
• Demonstrated hands-on experience with AWS Bedrock, SageMaker, Amazon OpenSearch Service, or equivalent cloud AI platforms.
• Demonstrated hands-on experience with Infrastructure as Code tools such as AWS CDK v2, Terraform, or CloudFormation.
• Demonstrated experience fine-tuning, evaluating, or optimizing foundation models and open-source LLMs.
• Demonstrated experience deploying containerized AI workloads using Docker and Kubernetes.
• Demonstrated experience building event-driven and serverless AI architectures using AWS Lambda, API Gateway, SNS, SQS, EventBridge, or Step Functions.
• Demonstrated experience implementing AI/ML data pipelines using AWS Glue, Athena, EMR, Spark, or equivalent technologies.
• Demonstrated experience with vector embeddings, semantic search, knowledge graphs, and enterprise search platforms.
• Demonstrated experience with orchestration platforms such as Airflow, Dagster, Kubeflow, MLflow, or Prefect.
• Demonstrated experience implementing MLOps pipelines for model training, validation, deployment, and monitoring.
• Demonstrated experience with feature stores, model registries, and experiment tracking platforms.
• Demonstrated experience working with DynamoDB, PostgreSQL, RDS, Hive, or NoSQL data platforms.
• Demonstrated experience with Parquet, ORC, Delta Lake, or Iceberg data formats and architectures.
• Demonstrated experience optimizing cloud infrastructure costs and AI workload performance.
• Demonstrated hands-on experience with Linux-based systems, shell scripting, and cloud-native operations.
• Experience implementing Responsible AI, model governance, security controls, and AI risk management frameworks.
• Experience working within government, defense, intelligence, or other highly regulated mission environments.
Company:
GCI is an Engineering and IT Services company focusing on Data Analytics, Engineering, Cyber Operations, Targeting and Analysis, Operations Solutions and Training. Founded in 1989, the company is headquartered in Reston, USA, with a team of 501-1000 employees. The company is currently Late Stage.