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Contextual Ai Jobs (NOW HIRING)

FastTek

Senior Cloud Database Engineer

Dearborn, MI

$97K - $132K/yr

Contextual AI Patterns: Define patterns for integrating Model Context Protocol (MCP) with databases for contextual AI interactions. * Intelligent Automation: Identify and implement AI-driven ...

Interon IT Solutions

ServiceNow AI Developer

Chantilly, VA · Remote

$55.25 - $76/hr

Integrate Model Context Protocol (MCP) to enable secure contextual AI interactions. * Implement multi-model and multi-agent orchestration frameworks. * Configure and optimize Now Assist, Predictive ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$50 - $55/hr

Engineer prompts and contextual workflows to improve LLM response quality and relevance. Implement robust AI response validation, guardrails, and monitoring mechanisms. Build intelligent solutions ...

CYNET SYSTEMS

AI Engineer

Atlanta, GA · On-site

$50 - $55/hr

Engineer prompts and contextual workflows to improve LLM response quality and relevance. * Implement robust AI response validation, guardrails, and monitoring mechanisms. * Build intelligent ...

Socket.dev

$184 - $257/hr

In this role, you will move beyond algorithm implementation to architecting the systems that power always-on contextual AI. This position sits at the intersection of Computer Vision, Embodied AI, and ...

Contextual.io

Senior Software Engineer - AI Solutions

$125K - $165K/yr

About Contextual Contextual partners with clients to deliver cutting-edge AI solutions that transform tasks, processes and operations with a focus on scale and ROI. By leveraging the Contextual.io ...

Contextual.io

Solution Delivery Lead

Lead the delivery of AI Solutions, built on the Contextual partners, for our clients. About Contextual Contextual partners with clients to deliver cutting-edge AI solutions that transform tasks ...

Hearst

Lead Engineer, Audience Data Platform

Manhattan, NY · Hybrid

$168K - $204K/yr

Partner with product managers and data scientists to evolve contextual AI and embedding models for privacy-safe, high-performance targeting. Qualifications (What We're Looking For) * 8+ years of ...

Hearst

Lead Engineer, Audience Data Platform

New York, NY · Hybrid

$168K - $204K/yr

Partner with product managers and data scientists to evolve contextual AI and embedding models for privacy-safe, high-performance targeting. Qualifications (What We're Looking For) * 8+ years of ...

WalkMe

Pre-Sales AI Consultant

New York, NY · On-site

Strong experience working with generative and contextual AI, including exposure to LLMs, AI architectures, deployment models, prompt development, and enterprise security considerations. * A minimum ...

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Contextual Ai information

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$31K

$97.1K

$172K

How much do contextual ai jobs pay per year?

As of Aug 17, 2026, the average yearly pay for contextual ai in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What is a contextual AI specialist?

Contextual AI specialists are professionals who design, develop, and implement artificial intelligence systems that understand and adapt to the context in which they operate. Their work involves creating models that can interpret data based on situational factors, user behavior, and environmental variables to provide more accurate and relevant outcomes. These specialists often collaborate with data scientists, software engineers, and domain experts to build AI solutions that deliver personalized user experiences and make informed decisions. Contextual AI is increasingly used in areas like natural language processing, recommendation systems, and smart assistants.

What are the key skills and qualifications needed to thrive as a contextual AI specialist?

To thrive as a Contextual AI Specialist, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Proficiency with AI development frameworks (like TensorFlow or PyTorch), data annotation tools, and experience with large language models are typically required. Critical thinking, problem-solving, and effective cross-functional communication help you interpret complex data and collaborate with stakeholders. These skills are essential to develop AI systems that understand and respond accurately to user context, ensuring relevance and reliability in real-world applications.

How do professionals working in contextual AI typically collaborate with cross-functional teams to deploy effective AI solutions?

Professionals in Contextual AI often work closely with data scientists, software engineers, product managers, and domain experts to develop and deploy AI models that understand and adapt to context-specific information. Collaboration commonly involves regular meetings to define project goals, align on data requirements, and iterate on model outputs based on feedback from stakeholders. Effective communication is crucial, as team members must translate complex AI concepts into actionable insights for non-technical colleagues. This multidisciplinary teamwork ensures that AI solutions are not only technically robust but also meet real-world user needs and business objectives.

What is the difference between Contextual Ai vs Data Analyst?

AspectContextual AiData Analyst
Required CredentialsBackground in AI, machine learning, data science, programmingDegree in statistics, mathematics, or related field; analytical skills
Work EnvironmentTech companies, AI development teams, research labsBusiness, finance, marketing departments, consulting firms
Industry UsageDeveloping AI models that understand context for automation and decision-makingInterpreting data, generating reports, providing insights for business strategies

Contextual Ai focuses on creating AI systems that understand and interpret context to improve automation and decision-making, often requiring advanced technical skills. Data Analysts analyze data to extract insights, supporting business decisions. While both roles work with data, Contextual Ai is more technical and development-oriented, whereas Data Analysts focus on data interpretation and reporting.

What does contextual AI do?

A role involving contextual AI focuses on developing and implementing artificial intelligence systems that understand and interpret information within specific contexts. This includes analyzing data, recognizing patterns, and adapting responses based on situational factors, often requiring skills in machine learning, natural language processing, and data analysis. Such work helps improve AI's relevance and accuracy in real-world applications.
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Contextual Ai jobs near you
Infographic showing various Contextual Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.

Capgemini Invent - Contextual Systems Engineer Senior Consultant

Capgemini

Dallas, TX • On-site

$103K - $141K/yr

Full-time

Re-posted 8 days ago

Capgemini North America rating

7.7

Company rating: 7.7 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

98th of 224 rated it services

Job description

Job Summary:
Capgemini is a global business and technology transformation partner, and they are seeking a Senior Consultant, Contextual Systems to join their Data Driven Transformation team. In this role, you will own defined workstreams within AI and data-driven transformation engagements, designing and implementing systems that enable AI to understand enterprise context while collaborating with client data teams.
Responsibilities:
• Designing and implementing semantic layer architectures end‑to‑end, including LookML models, dbt metrics, and ontologies
• Building knowledge graph schemas and implementing GraphRAG patterns for contextual AI retrieval
• Defining context contracts, including versioned semantic objects, governed datasets, and metric definitions
• Leading technical workshops to extract and encode enterprise knowledge into machine‑readable forms
• Evaluating and configuring knowledge platform tooling, including graph databases, vector stores, and embedding pipelines
• Partnering with AI engineering teams to integrate context layers into agentic and AI workflows
Qualifications:
Required:
• 5–6 years of experience in data engineering, data architecture, or knowledge management
• Hands‑on expertise with semantic layer tooling such as LookML, dbt, or equivalent technologies
• Experience designing and working with knowledge graphs (Neo4j preferred)
• Familiarity with modern LLM integration patterns, including RAG, embedding pipelines, and vector stores
• Strong ability to translate business semantics into formal, well‑governed technical specifications
Preferred:
• Experience working across cloud data platforms such as BigQuery or Snowflake
• Exposure to governance and catalog tooling (e.g., Collibra, Atlan)
• Interest in applied AI, agentic architectures, and enterprise‑scale contextual systems
Company:
Capgemini is a software company that provides consulting, technology, and digital transformation services. Founded in 1967, the company is headquartered in Paris, FRA, with a team of 10001+ employees. The company is currently Late Stage.

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