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Pinecone Vector Databases Jobs in Washington (NOW HIRING)

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 ...

Blue Origin

AI Engineer II - Blue Ring

Reston, VA

Familiarity with vector databases (e.g., Pinecone, pgvector, FAISS) and embedding model pipelines * Experience with time-series ML architectures (RNNs, LSTMs, Transformers) for forecasting or anomaly ...

CACI

Machine Learning Engineer

Chantilly, VA · On-site

$131K - $290K/yr

... vector databases (ChromaDB, Pinecone, Weaviate, or similar) for building intelligent retrieval systems Strong problem-solving abilities, attention to detail, excellent communication skills, and ...

Steampunk

Senior Data Engineer

Mclean, VA · On-site

$140K - $180K/yr

Experience with vector databases and embeddings for semantic search or retrieval use cases (e.g. Weaviate, Pinecone, PostgreSQL pgvector). * Familiarity with LLM-powered systems , including Retrieval ...

Steampunk

Senior Data Engineer

Mclean, VA · On-site

$140K - $180K/yr

Experience with vector databases and embeddings for semantic search or retrieval use cases (e.g. Weaviate, Pinecone, PostgreSQL pgvector). * Familiarity with LLM-powered systems , including Retrieval ...

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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.

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Pinecone Vector Databases jobs near you

Security Control Assessor/Representatives

Dark Wolf Solutions

Washington, DC • On-site

$135K - $150K/yr

Full-time

Re-posted 4 days ago

Job description

Dark Wolf Solutions is seeking Security Control Assessor/Representatives (SCA/Rs) to lead security control assessments across high-priority projects. Working at the intersection of cybersecurity engineering, cloud architecture, and DevSecOps prototyping, you will evaluate security controls for cutting-edge AI/LLM technologies across multiple classification levels. This position is ideal for a pragmatic cloud assessor or SCAR who excels in fast-paced DevSecOps environments, understands AWS cloud security, and is eager to shape the cybersecurity posture of next-generation DoD AI capabilities.This position will be based out of Arlington, VA with hybrid opportunities. Additional responsibilities include:
Key Responsibilities
  • Execute formal SCA/R duties.
  • Lead security assessment efforts, establishing reusable security playbooks and assessment frameworks for rapid AI deployment into enterprise workflows.
  • Evaluate technical control effectiveness across AWS cloud infrastructure, DevSecOps pipelines, microservices, containerized workloads, and GenAI/LLM application stacks.
  • Partner directly with cybersecurity engineering and DevSecOps prototyping teams to integrate security controls early in the development lifecycle.
  • Review, author, and maintain assessment packages-including System Security Plans (SSPs), Security Assessment Plans (SAPs), Security Assessment Reports (SARs), and POA&Ms-tailored to rapid prototyping and AI systems.
  • Assess technical security risks specific to AI/LLM implementations, such as API exposure, vector database access controls, model integration surface area, and software supply chain dependencies.
  • Support continuous monitoring (ConMon), technical risk evaluations, and cloud architecture reviews across multi-tenant, multi-classification environments.
  • Coordinate with Authorizing Officials (AOs), program managers, and engineering leads to deliver decision-ready risk briefings and ATO recommendations.
  • Provide technical input and oversight for cybersecurity engineering and penetration testing activities across prototype projects.

Required Qualifications
  • Active Top Secret security clearance
  • Current DoD 8570/8140 IAM Level II or Level III certification (e.g., Security+, CySA+, CISM, CISSP, CCISO, CAP/CISC)
  • 3-5+ years of experience conducting security control assessments, compliance testing, or A&A/RMF activities for DoD or federal information systems
  • Solid operational understanding of core AWS cloud services (EC2, S3, IAM, VPCs, Security Groups, Security Hub) and how security controls function within cloud-native and CI/CD pipeline environments.
  • Strong working knowledge of NIST SP 800-53 (Rev. 4/5), NIST SP 800-37 (RMF), DoD Cloud Computing SRG, and FedRAMP baselines.
  • Demonstrated experience writing and evaluating core RMF artifacts (SSPs, SAPs, SARs, POA&Ms)
  • Exceptional written and verbal communication skills, with the ability to articulate technical risk clearly to executive stakeholders, Authorizing Officials, and engineering teams.
  • Hands-on experience navigating government GRC repositories, such as eMASS or XACTA.

Desired Qualifications
  • Hands-on experience mapping security controls to the NIST AI Risk Management Framework (AI RMF), the OWASP Top 10 for LLM Applications, or the DoD Responsible AI (RAI) Guidelines.
  • Familiarity evaluating secure design patterns for autonomous AI Agents (e.g., tool-calling permissions, sandboxing agent execution environments, prompt boundaries, and ReAct/LangGraph architectures).
  • Experience assessing cloud-managed AI ecosystems and foundation model platforms (e.g., AWS Bedrock, AWS SageMaker, Hugging Face Enterprise, or self-hosted open-source models).
  • Understanding of data protection, access controls, and boundary security for RAG pipelines and vector databases (e.g., OpenSearch Vector Engine, Pinecone, Milvus, or PostgreSQL pgvector).
  • Familiarity evaluating risks unique to LLMs-including prompt injection, data poisoning, model inversion, insecure output handling, and open-source supply chain vulnerabilities in AI libraries (PyTorch, LangChain, LlamaIndex).
  • Exposure to LLM guardrail platforms, evaluation frameworks, or AI security tools (e.g., Promptfoo, Garak, Giskard, NeMo Guardrails) used to test model robustness and output safety.
  • Experience with cATO methodologies, Infrastructure as Code (IaC) templates (Terraform, CloudFormation), and container security (AWS EKS/ECS, Docker).
  • Active AWS Certifications (e.g., AWS Certified Security - Specialty or AWS Certified Solutions Architect).
  • Background or familiarity with offensive security, penetration testing

The salary range for this position is estimated to be between $135,000.00 - $150,000.00, commensurate on experience and technical skillset.
We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.
In compliance with federal law, all persons hired will be required to verify identity, confirm US Citizenship, and complete the required employment eligibility verification upon hire.
We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.

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