AI Architect

Bespoke Technologies; Vienna (VA); On-site; USD 140,000 - 180,000; Full time

Job summary

Bespoke Technologies is seeking an experienced AI Architect to design, prototype, and implement advanced AI and GenAI solutions at Tysons Corner, VA. You will work with data scientists, engineers, and stakeholders to translate requirements into scalable AI architectures.

The role emphasizes Python development, LLM/GenAI architectures, OCR, embeddings, knowledge graphs, APIs, and AWS services. Collaboration with senior customers is essential.

Qualifications

• Strong Python development skills.
• Deep understanding of LLMs and GenAI architectures.
• Experience designing AI systems that integrate data, APIs, cloud services, AI agents, and GenAI capabilities.
• Familiarity with OCR, embeddings, vector databases, and knowledge graphs.

Responsibilities

• Design, architect, and prototype AI and GenAI solutions for complex requirements.
• Develop AI architectures leveraging LLMs, GenAI, AI agents, and modern AI services.
• Develop Python-based AI engineering, data processing, integrations, and prototyping.
• Apply prompt engineering to optimize LLM performance.
• Understand LLM context windows, tokenization, embeddings, and embedding models.
• Design and implement AI agents, orchestration, tool calling, and function calling.
• Configure and interact with MCP servers for external tools and data.
• Design and integrate APIs for AI applications and data sources.
• Incorporate OCR capabilities and develop knowledge graphs for reasoning.
• Design architectures with embedding models, vector databases, semantic search, and retrieval-based AI.
• Create AI-powered chatbots and conversational interfaces.
• Develop source traceability and verification mechanisms to reduce AI hallucinations.
• Evaluate data to determine preparation methods for AI systems.
• Design ETL pipelines, data lakes, and streaming data solutions.
• Understand data schemas/models and their role in AI/data processing.
• Work with NiFi and Airflow for data orchestration.
• Design and deploy AWS-based AI solutions (S3, EC2, IAM, VPC, Bedrock).
• Assess data holdings and mission use cases to decide AI architectures.

Skills

Python

LLMs

GenAI

OCR

Knowledge graphs

APIs

Prompt engineering

Context windows

Embedding models

Agents

Tool calling

MCP servers

AWS cloud architecture

ETL pipelines

Data lakes

Streaming data

Apache NiFi

Airflow

Data schemas

Education

Bachelor's degree in Computer Science, Engineering, Data Science, AI, or related field

Tools

Apache NiFi

Airflow

AWS Bedrock

S3

EC2

IAM

VPC

Vector databases

Semantic search

Embeddings

OCR technologies

Knowledge graphs

Job description

AI Architect

Location: Tysons Corner, VA

BT-429 – AI Architect

Location: Tysons, VA

Bespoke Technologies is seeking an experienced AI Architect to design, architect, prototype, and implement advanced Artificial Intelligence and Generative AI solutions supporting mission-critical data and technology initiatives. The AI Architect will work closely with senior mission stakeholders, data scientists, software engineers, and technical teams to translate complex requirements into scalable AI architectures and solutions.

The ideal candidate will possess strong Python development skills, a deep understanding of LLMs and Generative AI architecture, and experience designing AI systems that integrate data, APIs, cloud services, AI agents, and modern GenAI capabilities. The role requires a strong understanding of how AI systems interact with structured and unstructured data, including OCR, knowledge graphs, embeddings, vector-based architectures, and data pipelines.

Responsibilities

• Design, architect, and prototype AI and Generative AI solutions that address complex mission and customer requirements.
• Develop AI architectures leveraging Large Language Models (LLMs), Generative AI, AI agents, and modern AI services.
• Develop solutions using Python for AI engineering, data processing, integrations, and prototyping.
• Apply prompt engineering techniques to optimize LLM performance and develop effective AI applications.
• Understand LLM context windows, tokenization, embeddings, and embedding models and how they impact AI application design.
• Design and implement AI agents, including agent orchestration, tool calling, and function calling.
• Configure, integrate, and interact with MCP (Model Context Protocol) servers to provide AI systems with access to external tools, services, and data.
• Design and integrate APIs supporting AI applications and interactions between services, models, and data sources.
• Incorporate OCR capabilities into AI architectures for extracting and processing information from documents and other unstructured data.
• Develop and leverage knowledge graphs, including an understanding of entities, relationships, and how they can support AI reasoning and information retrieval.
• Design architectures incorporating embedding models, vector databases, semantic search, and retrieval-based AI approaches.
• Design and integrate AI-powered chatbot and conversational interfaces.
• Develop mechanisms for source traceability, information verification, and reduction of AI hallucinations.
• Evaluate structured and unstructured data and determine the appropriate approach for preparing and making data available to AI systems.
• Design solutions that integrate ETL pipelines, batch processing, data lakes, and streaming data.
• Develop an understanding of data schemas and data models and how they support AI and data processing systems.
• Work with data ingestion and orchestration technologies such as Apache NiFi and Airflow.
• Design and deploy AI solutions using AWS cloud architecture, including services such as S3, EC2, IAM, VPC, Amazon Bedrock, and related AWS services.
• Evaluate existing data holdings, technical environments, and mission use cases to determine appropriate AI architecture and data strategies.
• Collaborate directly with high-level and senior customers to understand mission needs, communicate technical concepts, and recommend appropriate AI solutions.
• Lead technical discussions and communicate complex AI architecture concepts to both technical and non-technical stakeholders.
• Prototype and evaluate emerging AI technologies and determine their applicability to mission requirements.

Here is what you need:

• Strong Python
• Understanding of LLMs / GenAI architecture
• Understanding of OCR
• Understanding of Knowledge graphs and entities/relationships
• APIs
• Prompt Engineering
• Context Windows and Tokenization
• Embedding Models
• Agents and tool callingSetting up and hitting MCP Servers
• Function calling
• Good understanding of Cloud Architecture with AWS (S3, EC2, IAM, VPC, Bedrock, etc...)
• Understanding of ETL Pipeline and Batch Processing
• Data Lakes
• Streaming data
• NiFi and Airflow
• Understand data schemas / models

Ability to work with high level/senior customers

Bonus if you have:

• Experience developing or deploying GenAI agents in mission-driven environments.
• Experience with vector databases and semantic search.
• Experience with AI model optimization and evaluation.
• Experience designing cloud-native AI platforms and distributed systems.
• Experience implementing source traceability and verification mechanisms for AI-generated content.
• Experience with data cataloging, metadata management, and knowledge management.
• Experience with Java or other modern programming languages.
• AI, cloud, data science, or software engineering certifications.

Education:

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical field.