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Associate Ai Engineer Jobs (NOW HIRING)

As an Associate AI Engineer on the IT AI team, you will work alongside our team of talented engineers to build GenAI agents, optimize LLM prompts, implement RAG pipelines, and integrate AI with our ...

Associate AI Engineer Location :โ€ƒโ€ƒHybrid, United States Employment Type :โ€ƒFull-Time Benefits Offered :โ€ƒVision, Medical, Life, Dental, 401K Gross Annual Base Salary :โ€ƒUSD 87,000 - 116,000 ...

Associate AI Engineer Location :โ€ƒโ€ƒHybrid, United States Employment Type :โ€ƒFull-Time Benefits Offered :โ€ƒVision, Medical, Life, Dental, 401K Gross Annual Base Salary :โ€ƒUSD 87,000 - 116,000 ...

Associate AI Engineer Location :Hybrid, United States Employment Type :Full-Time Benefits Offered :Vision, Medical, Life, Dental, 401K Gross Annual Base Salary :USD 87,000 - 116,000 Additional ...

Associate AI Engineer Location :โ€ƒโ€ƒHybrid, United States Employment Type :โ€ƒFull-Time Benefits Offered :โ€ƒVision, Medical, Life, Dental, 401K Gross Annual Base Salary :โ€ƒUSD 87,000 - 116,000 ...

Associate AI Engineer Location :โ€ƒโ€ƒHybrid, United States Employment Type :โ€ƒFull-Time Benefits Offered :โ€ƒVision, Medical, Life, Dental, 401K Gross Annual Base Salary :โ€ƒUSD 87,000 - 116,000 ...

They are seeking an Associate AI Engineer to build AI-powered applications, develop evaluation frameworks, and optimize data pipelines while working within collaborative and flexible culture.

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KPMG is currently seeking an Associate, AI Engineer to join our Consulting practice. Responsibilities: * Develop GenAI / LLM applications and integrations using foundational models under the guidance ...

KPMG is currently seeking an Associate, AI Engineer to join our Advisory Services practice. Responsibilities: * Develop GenAI / LLM applications and integrations using foundational models under the ...

The AI Engineer is an entry-level engineering role designed for early-career technologists who are passionate about artificial intelligence and software engineering. In this role, you will work ...

Associate AI Engineer

Chicago, IL ยท On-site

$85K/yr

Role Overview We are seeking Forward-Deployed AI Engineers to rapidly prototype AI solutions in real-world advisor workflows. This role is embedded in our discovery team, working alongside Product ...

Build end-to-end AI-powered applications (UI + backend services + model orchestration) * Design and ... Support experimentation (prompt engineering, model comparisons, fine-tuning readiness) Data ...

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Associate Ai Engineer information

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$41.5K

$82.6K

$132K

How much do associate ai engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for associate ai engineer in the United States is $82,636.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,500.00 and $95,000.00 per year, depending on experience, location, and employer.

What does an Associate AI Engineer do?

An Associate AI Engineer assists in designing, developing, and implementing artificial intelligence models and applications. They typically work under the guidance of senior engineers to build machine learning algorithms, preprocess data, and test AI solutions. Their responsibilities often include writing code, evaluating model performance, and collaborating with data scientists and software developers. This entry-level role provides hands-on experience in AI technologies and helps build a foundation for more advanced engineering positions.

What are the key skills and qualifications needed to thrive as an Associate AI Engineer, and why are they important?

To thrive as an Associate AI Engineer, you need a solid understanding of programming (especially Python), mathematics (linear algebra, probability, statistics), and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with cloud platforms such as AWS or Google Cloud are typically required. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help distinguish top performers in this role. These skills and qualities are essential for successfully developing, implementing, and maintaining AI solutions in a collaborative and rapidly evolving environment.

What is the difference between Associate Ai Engineer vs Data Scientist?

AspectAssociate Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, startups, R&D teams; focus on AI model developmentResearch labs, tech firms, finance; focus on data analysis and modeling
Employer & Industry UsageAI-focused roles in tech, healthcare, financeData analysis across industries like marketing, finance, healthcare

Associate Ai Engineers typically focus on developing and implementing AI models, often working closely with data and algorithms. Data Scientists analyze large datasets to extract insights and build predictive models. While both roles require programming skills and a background in data or AI, Associate Ai Engineers are more involved in the technical development of AI systems, whereas Data Scientists focus on data analysis and interpretation.

What are some common challenges an Associate AI Engineer may face when working on real-world machine learning projects?

As an Associate AI Engineer, you may encounter challenges such as handling imperfect or limited datasets, balancing model performance with computational constraints, and integrating AI solutions into existing products. Collaboration with data scientists, software engineers, and product managers is crucial to refine objectives and ensure technical feasibility. Additionally, keeping up with evolving AI frameworks and best practices can be demanding, but it provides valuable learning opportunities and skill growth.
More about Associate Ai Engineer jobs
What cities are hiring for Associate Ai Engineer jobs? Cities with the most Associate Ai Engineer job openings:
What are the most commonly searched types of Ai Engineer jobs? The most popular types of Ai Engineer jobs are:
What states have the most Associate Ai Engineer jobs? States with the most job openings for Associate Ai Engineer jobs include:
Infographic showing various Associate Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, 32% Part Time, and 1% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $82,636 per year, or $39.7 per hour.
Associate AI Engineer

Associate AI Engineer

Kaleris

Alpharetta, GA โ€ข On-site

Full-time

Posted 7 days ago


Job description

Job Description:

As an Associate AI Engineer on the IT AI team, you will work alongside our team of talented engineers to build GenAI agents, optimize LLM prompts, implement RAG pipelines, and integrate AI with our enterprise applications. You will work on Microsoft Azure AI Foundry, Anthropic Claude, contributing to the AVA AI platform that powers AI features across Kaleris.

This is a hands-on engineering role, not a support or QA position. You will write production code, instrument token telemetry, design data schemas, and ship features. Equally important - you will engage with business stakeholders to understand their workflows, gather requirements, and help determine whether AI is the right tool for the job. Sometimes the best solution isn't AI at all, and we value engineers who can think that way.

The Role

As an Associate AI Engineer on the IT AI team, you will work alongside senior engineers to build GenAI agents, optimize LLM prompts, implement RAG pipelines, and integrate AI with our enterprise applications. You will work on Microsoft Azure AI Foundry with Anthropic Claude, contributing to the AVA AI platform that powers AI features across Kaleris.

This is a hands-on engineering role, not a support or QA position. You will write production code, instrument token telemetry, design data schemas, and ship features. Equally important - you will engage with business stakeholders to understand their workflows, gather requirements, and help determine whether AI is the right tool for the job. Sometimes the best solution isn't AI at all, and we value engineers who can think that way.

A master's-level background in AI/ML, data science, or computer science will help you ramp quickly and contribute meaningfully.

Our Technology Stack
  • AI Platform:Microsoft Azure AI Foundry, Azure OpenAI Service, Anthropic Claude
  • Frameworks:LangChain, Semantic Kernel, LlamaIndex
  • Data & Backend:PostgreSQL, Prisma ORM, Docker
  • Development & CI/CD:Python, TypeScript, GitHub, GitHub Actions
  • Enterprise Applications:Salesforce, NetSuite, Workday, Navan, Certinia and more...
  • Security & Compliance:Wiz, Vanta, 1Password, Conductor1
What You'll Do

Engineering & Development

  • Build GenAI agents and AI-powered workflows on Azure AI Foundry and with Anthropic Claude APIs under senior engineer guidance
  • Write, test, and optimize prompts for LLMs - including system prompts, few-shot examples, and tool-calling specifications - with a focus on token efficiency and output quality
  • Instrument AI calls with token usage logging; contribute to per-user and per-workflow token telemetry dashboards in Azure Monitor
  • Implement RAG pipeline components: document ingestion, embedding generation, vector store upsert (Azure AI Search), and retrieval quality evaluation
  • Build and maintain AI-native PostgreSQL schemas using Prisma ORM: prompt history, token audit logs, embedding metadata, and evaluation records
  • Write integration code connecting AI workflows to Salesforce, NetSuite, and Workday via REST APIs
  • Package and deploy AI microservices using Docker; contribute to GitHub Actions CI/CD pipelines
  • Follow secure development practices: secret management with 1Password, PII handling in prompts and outputs, prompt injection awareness
  • Write technical documentation for prompt patterns, integration designs, and AI feature implementations

Business Engagement & Problem Solving

  • Partner with business stakeholders across the organization to understand current workflows, gather requirements, and identify where technology can add meaningful value
  • Analyze business problems with an open mind - propose AI-powered solutions where appropriate, but recognize and recommend conventional engineering, process improvements, or configuration changes when those are the better fit
  • Translate business needs into clear technical requirements and work with cross-functional technical teams (infrastructure, enterprise apps, data) to design and implement solutions
  • Participate in discovery conversations and requirements sessions, asking the right questions to surface root causes, not just symptoms
  • Develop a working knowledge of Kaleris business processes - supply chain execution, terminal operations, logistics workflows - to become a more effective solution partner over time
What You Bring

Technical Skills

  • Degree in Computer Science, AI/ML Engineering, Data Science, or related technical field
  • Strong Python proficiency - clean, testable, production-quality code
  • Foundational knowledge of LLMs, prompt engineering, and GenAI system design through coursework, research, or projects
  • Familiarity with REST APIs and ability to write and read API integration code
  • Working knowledge of Git and basic CI/CD concepts

Communication & Collaboration

  • Strong written and verbal communication skills; able to translate technical concepts for non-technical audiences and business context for technical teams
  • Proven ability to gather and document requirements from stakeholders with varying levels of technical background
  • Comfort facilitating or participating in discovery sessions, asking clarifying questions, and synthesizing what you hear into actionable problem statements
  • Collaborative mindset - you work well across teams, share context proactively, and know when to escalate

Soft Skills & Mindset

  • Curiosity and eagerness to learn- you actively seek to understandwhya business process works the way it does before proposing how to change it
  • Adaptability- you're comfortable moving between a coding problem in the morning and a stakeholder conversation in the afternoon
  • Problem-first thinking- you resist the urge to default to AI as the answer; you evaluate the problem first and select the right tool for the job
  • Ownership- you follow through, communicate blockers early, and take accountability for your deliverables
  • Resilience and coachability- you welcome feedback, iterate without defensiveness, and grow from it
  • Attention to detail- in both code quality and in capturing what stakeholders actually need, not just what they say they need
  • Positive, team-oriented attitude- you contribute to a culture where people help each other succeed
Preferred Qualifications
  • Hands-on experience with Azure, AWS, or GCP AI/ML services
  • Experience with LangChain, LlamaIndex, or Semantic Kernel
  • Exposure to vector databases (Azure AI Search, Pinecone, Weaviate, Chroma)
  • Experience with PostgreSQL and an ORM (Prisma, SQLAlchemy, or equivalent)
  • Basic Docker and containerized deployment experience
  • Experience in requirements gathering, business analysis, or solution design - even informally (e.g., academic projects, internships, or consulting)
  • AI/ML research, hackathon, or open-source project participation
  • Familiarity with supply chain, logistics, or enterprise SaaS environments is a plus

Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.