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Pinecone Vector Databases Jobs in Washington, DC

Karsun Solutions, LLC

Lead Data Architect

Herndon, VA · On-site

$160K - $190K/yr

Experience integrating Databricks with vector databases (Pinecone, neo4j) and retrieval frameworks (LangChain, LlamaIndex). * Familiarity with AWS Bedrock or other managed LLM services. * Experience ...

Karsun Solutions, LLC

Lead Data Architect

Herndon, VA

$160K - $190K/yr

Experience integrating Databricks with vector databases (Pinecone, neo4j) and retrieval frameworks (LangChain, LlamaIndex). * Familiarity with AWS Bedrock or other managed LLM services. * Experience ...

Avancer Corporation

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

Experience with vector databases such as PG Vector or Pinecone. * Background in document processing pipelines, including OCR and PDF parsing. * Experience with cloud platforms such as AWS, Google ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

... vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

... vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and ...

Trilagen

Agentic AI Engineer

Mclean, VA · On-site

... vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and ...

Trilagen

Agentic AI Engineer

Mclean, VA · On-site

... vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and ...

Trilagen

Agentic AI Engineer

Bethesda, MD · On-site

... vector databases (Pinecone, pgvector, OpenSearch, Weaviate), semantic search, and hybrid retrieval strategies. You know when to use each and how to keep them performant at scale. Security and ...

Amtex Systems Inc

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

Experience with vector databases such as PG Vector or Pinecone. * Background in document processing pipelines, including OCR and PDF parsing. * Experience with cloud platforms such as AWS, GCP, or ...

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Pinecone Vector Databases information

What is a Pinecone vector database?

A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.

What are the key skills and qualifications needed to thrive as a Pinecone vector database engineer, and why are they important?

To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.

What are some common challenges faced by engineers working with Pinecone vector databases, and how can they be addressed?

Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.

What is the difference between Pinecone Vector Databases vs Data Engineers?

AspectPinecone Vector DatabasesData Engineers
Primary RoleManaging and deploying vector database solutions for AI/ML applicationsDesigning, building, and maintaining data pipelines and infrastructure
Skills & CertificationsKnowledge of vector databases, cloud platforms, programming (Python, SQL)Data modeling, ETL processes, cloud services, programming (Python, Java)
Work EnvironmentTech companies, AI startups, cloud providersData-driven organizations, tech firms, finance, healthcare

While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.

What are popular job titles related to Pinecone Vector Databases jobs in Washington, DC?

For Pinecone Vector Databases jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Pinecone Vector Databases jobs in Washington, DC look for?

The top searched job categories for Pinecone Vector Databases jobs in Washington, DC are:

Pinecone Vector Databases jobs near you
Infographic showing various Pinecone Vector Databases job openings in Washington, DC as of June 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Lead Data Architect

Karsun Solutions, LLC

Herndon, VA • On-site

$160K - $190K/yr

Full-time

Re-posted 17 days ago

Job description

Why Karsun?
Join Karsun Solutions to grow your career with the company transforming possible for the US Government.
At Karsun, collaboration drives our community. We're committed to building an environment where team members from diverse backgrounds can innovate, learn and grow with us. Here at Karsun, the only limit to your potential is the limit of your curiosity.
Join Team Karsun, and Find Your Next!
Summary
The Lead Data Architect will design, build, and operate enterprise data platforms that power GenAI and AI/ML use cases. This is a highly technical, hands-on role responsible for data platform architecture, end-to-end data engineering, ML/LLM pipeline design, production model onboarding, and delivery of scalable Databricks- centric solutions across cloud environments.
What You'll Be Doing:
  • Architect and implement enterprise data platforms (batch + streaming) optimized for ML, LLMs, and GenAI workloads.
  • Lead design and hands on implementation of Databricks workspaces, Unity Catalog, Delta Lake design patterns, cluster policies, and performance tuning.
  • Build and own end to end data pipelines (ingest, transform, feature engineering, serving) using PySpark, Databricks Jobs, Spark SQL, Delta Lake, and orchestration tools.
  • Design and operationalize model training, fine tuning (LLM), evaluation, deployment, and monitoring pipelines (MLOps/RAG/CAG) integrating Databricks MLflow, CI/CD, and infra-as-code.
  • Implement vectorless and vectorization/embedding pipelines, vector store integrations, and retrieval layers for RAG (FAISS, Pinecone, Weaviate, Milvus).
  • Define data schemas, governance, lineage, access controls, and data product APIs; implement Unity Catalog or equivalent for centralized governance.
  • Drive cost/performance optimization for storage, compute (spot/preemptible),and query patterns.
  • Collaborate with engineers, data scientists, product owners, and security to translate business needs into production GenAI solutions.
  • Mentor and lead engineering teams; conduct architecture reviews, code reviews, and run technical deep dives.
  • Implement observability for data and ML pipelines (metrics, logging, data quality tests, alerting).
  • Create reproducible experiment tracking, model registry, and rollout strategies (canary, shadow testing, rollback).
  • Stay current on GenAI/LLM architectures and evaluate/introduce new tooling and frameworks.

Required Qualifications:
  • BA or BS degree in CS, Computer Engineering, Information Technology or a
    related field.
  • 8+ years hands on experience in data engineering/platform architecture; 3+ years in an architect or lead role.
  • Candidate must hold an active AWS Certified Machine Learning - Specialty certification or equivalent AWS certification.
  • Proven, hands on Databricks experience (designing workspaces, Delta Lake, performance tuning, productionizing Spark jobs).
  • Deep Spark + PySpark expertise and experience with Databricks Runtime.
  • Strong experience building ML/LLM pipelines and operationalizing models (training, fine tuning, serving).
  • Practical experience with vector embeddings, semantic search, and RAG architectures.
  • Solid Python expertise and common ML libraries (PyTorch, TensorFlow, Hugging Face transformers) and MLflow.
  • Cloud platform experience (AWS strongly preferred).
  • Experience with containerization and orchestration while leveraging open source libraries for unstructured and structured data processing, serving/inference.
  • Strong SQL skills; experience with distributed query/warehouse systems and parquet/AVRO/Delta formats.
  • CI/CD and infra-as-code experience (Terraform, GitOps, Jenkins/GitHub Actions/GitLab CI).
  • Data governance, security, and IAM experience; experience implementing row/column level access controls and data lineage.
  • Demonstrated ability to design for scalability, reliability, and cost efficiency.

Preferred Qualifications:
  • Prior experience with Databricks Unity Catalog, Photon, and Databricks SQL.
  • Experience integrating Databricks with vector databases (Pinecone, neo4j) and retrieval frameworks (LangChain, LlamaIndex).
  • Familiarity with AWS Bedrock or other managed LLM services.
  • Experience with realtime streaming (Kafka, Kinesis) and stream processing on Databricks Structured Streaming.
  • Certifications: Databricks Certified Professional.
  • Experience with data quality and profiling tools (Great Expectations, Soda).
  • Experience with large-scale ETL frameworks and tools (Airflow, Prefect).

Things to Know:
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
Salary Range
The proposed salary range for this role is $160,000 to $190,000 USD. The salary range provided is a good faith estimate representative of all experience levels. Karsun considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.
Third Party Resumes: Karsun does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Karsun and Karsun will not be obligated to pay a placement fee.
Clearance Information
This position requires the eligibility to obtain a security clearance. The Defense Industrial Security Clearance Office (DISCO), an agency of the Department of Defense, handles and adjudicates the security clearance process. More information about Security Clearances can be found on the US Department of State government website: https://www.state.gov/m/ds/clearances/c10978.htm
Location
To be considered for this role, you must reside in one of the following states: CA, CO, DC, FL, GA, IL, MD, NJ, NY, NC, OH, OK, PA, SC, TX, VA, WV.
Work Authorization
Applicants must be authorized to work in the U.S. We may consider candidates currently in H-1B status who are eligible for transfer.
Statement on AI and Hiring Process
At Karsun, we are committed to a fair and equitable hiring process. We do not use artificial intelligence to make decisions on candidates, scan resumes, or source potential hires. Applicants are reviewed by our talent acquisition team and hiring managers to ensure a thorough evaluation based on skills, experience, and alignment with our company values. Our hiring decisions are made with human judgement, ensuring fairness and transparency throughout the process.

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