Description

Position Details: 

Job Title: Database Architect (Cloud, AI & LLM Platforms) 

Job Type: Full-time 

Location: Remote, MD  

Dynanet Corporation Overview: 

Dynanet started with a focus on IT infrastructure and operations, helping organizations enhance their networks and overcome the limitations of 1990s technology. From strengthening communication channels to introducing innovative ways to collaborate and share information, Dynanet played a crucial role in shaping the early stages of digital transformation. The company’s efforts helped organizations build the very fabric of connectivity that now powers our modern world. Over the last three decades, Dynanet has grown into a trusted partner for organizations looking to innovate boldly and transform seamlessly. While technology continues to evolve and unlock new opportunities, for nearly 30 years, Dynanet remains committed to delivering cutting-edge solutions that drive lasting change for its customers. Through agility, foresight, and an unwavering dedication to excellence, Dynanet continues to empower organizations to thrive in a rapidly changing digital landscape. Our story is more than just a story of technology – it’s a story of vision, growth, and transformation that has shaped the past and continues to pave the way for the future. 

About the Role: 

We are seeking an experienced Database Architect to design, build, and optimize cloud-based data platforms that support traditional enterprise workloads as well as modern AI and Large Language Model (LLM) applications. This role requires deep, hands-on expertise across relational, NoSQL, and vector databases, with a strong focus on scalability, performance, security, and reliability in the cloud. 

The ideal candidate is equally comfortable designing data models, tuning queries, enabling semantic search and embeddings, and collaborating with data science and AI engineering teams. 

Roles & Responsibilities: 

• Architect, design, and implement cloud-native database solutions across relational, NoSQL, and vector database technologies. 
• Lead database strategy and standards to support AI/ML and LLM workloads, including embeddings, semantic search, and retrieval-augmented generation (RAG). 
• Design and optimize data models, schemas, indexing strategies, and storage patterns for performance and scalability. 
• Build and manage vector databases to support similarity search, recommendations, and AI inference pipelines. 
• Collaborate with AI/ML engineers, application developers, and platform teams to integrate databases into end-to-end systems. 
• Ensure high availability, disaster recovery, security, and compliance across all database platforms. 
• Optimize cost, performance, and reliability in cloud environments. 
• Implement monitoring, alerting, backup, and automation for database operations. 
• Provide technical leadership, documentation, and best-practice guidance to engineering teams. 
• Evaluate and recommend new database technologies and cloud services as requirements evolve. 

Required Professional Skills: 

• 7+ years of hands-on experience designing and supporting enterprise-scale database systems. 
• Strong expertise in relational databases (e.g., PostgreSQL, MySQL, Oracle, SQL Server, Amazon Aurora). 
• Hands-on experience with NoSQL databases (e.g., MongoDB, DynamoDB, Cassandra, Couchbase). 
• Practical experience with vector databases and similarity search (e.g., Pinecone, Milvus, Weaviate, pgvector, OpenSearch/Elastic vector search). 
• Experience supporting AI/LLM applications, including embeddings, RAG architectures, and inference pipelines. 
• Strong SQL skills and solid understanding of query optimization and performance tuning. 
• Experience with cloud platforms (AWS, Azure, and/or Google Cloud). 
• Knowledge of data security, encryption, access controls, and compliance requirements. 
• Ability to translate business and application requirements into scalable data architectures. 

Preferred Professional Skills: 

• Experience with LLM platforms (e.g., OpenAI, Azure OpenAI, Amazon Bedrock, Hugging Face). 
• Familiarity with data pipelines, streaming, or analytics platforms (e.g., Kafka, Spark, Snowflake, BigQuery). 
• Infrastructure-as-Code experience (Terraform, CloudFormation, ARM). 
• Experience with DevOps or DataOps practices. 
• Background in designing high-throughput, low-latency systems. 
• Cloud certifications (AWS, Azure, or GCP) are a plus. 

Dynanet Team Requirements and Expectations: 

• Possess Strong written and verbal communication skills. 
• Highly organized with an ability to prioritize, balance, and effectively advance multiple competing priorities in a high-volume, fast-paced environment. 
• Ability to interact in a professional and collaborative manner with fellow Dynanet Teammates and the clients, and business partners that we work with. 
• Ability and desire to challenge and educate yourself to support and advance IT services delivery in the Federal agencies we serve. 
• Excellent judgment and creative problem-solving skills. 
• Respond to team member and client requests via email, MS teams, or other communication means during core business hours. 
• Active listening skills to understand clients' needs, and collaboration skills to work with other developers and designers. 

Education/Experience Requirements: 

• Bachelor’s degree in Computer Science, Information Technology, or related field. 
• 7+ years of hands-on experience designing and supporting enterprise-scale database systems. 
• Hands-on experience with NoSQL databases (e.g., MongoDB, DynamoDB, Cassandra, Couchbase). 
• Practical experience with vector databases and similarity search (e.g., Pinecone, Milvus, Weaviate, pgvector, OpenSearch/Elastic vector search). 
• Experience supporting AI/LLM applications, including embeddings, RAG architectures, and inference pipelines. 
• Experience with cloud platforms (AWS, Azure, and/or Google Cloud).

Employee Benefits Overview: 

• Industry Competitive Compensation 
• Medical and Dental Insurance 
• Paid Time Off/Holidays 
• 401(k) Retirement Plans with Matching 
• Remote Work* 
• Paid Training 
• Employee Referral Program
• Employee Development Program