AI Engineer – Cloud Software & AI Platforms - Contract
Confirmed on the employer's own hiring board on Oct 10, 2026. First seen by Alion on Aug 21, 2026. Altera scores A on the Alion truth index.
Job Details:
Job Description:
AI Engineer - Cloud Software & AI Platforms- Contract
Team: Cloud Software Engineering - Quartus AI, Altera
About the Role
We are seeking a highly motivated AI Engineer to join our Cloud Software Engineering team. In this role, you will help design, develop, and optimize AI-powered applications and intelligent services that improve developer productivity, knowledge discovery, and engineering workflows. You will work across machine learning, large language models (LLMs), search technologies, data pipelines, and cloud-native platforms to deliver scalable AI solutions for internal and external users.
This is an opportunity to work at the intersection of AI, cloud computing, and software engineering, collaborating with cross-functional teams to build next-generation intelligent systems.
Key Responsibilities
Design and develop AI and machine learning solutions that leverage modern LLMs, retrieval systems, and agent-based architectures.
Design, build, and optimize agentic AI workflows that coordinate LLMs, tools, enterprise data sources, APIs, and multi-step reasoning to automate complex engineering and knowledge-discovery tasks.
Build and optimize data processing, indexing, and retrieval pipelines to enable intelligent search and knowledge discovery.
Develop evaluation frameworks, benchmarks, and monitoring solutions to measure system quality, accuracy, and user impact.
Experiment with model selection, prompt engineering, retrieval strategies, ranking approaches, and fine-tuning techniques.
Analyze system performance, identify gaps, and drive continuous improvements using data-driven methodologies.
Collaborate with software engineers, product teams, and domain experts to translate business requirements into scalable AI solutions.
Develop and maintain cloud-native services and APIs supporting AI applications.
Contribute to architecture, design reviews, and engineering best practices across the AI platform.
Stay current with advancements in generative AI, machine learning, and information retrieval technologies.
The pay range below is for Bay Area California only. Actual salary may vary based on a number of factors including job location, job-related knowledge, skills, experiences, trainings, etc. We also offer incentive opportunities that reward employees based on individual and company performance.
$118.9K - $172.2K USD
We use artificial intelligence to screen, assess, or select applicants for the position. Applicants must be eligible for any required U.S. export authorizations.
Qualifications:
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field.
3+ years of industry experience in software engineering, machine learning, data science, or related disciplines.
Strong programming skills in Python, typescript, and familiarity with modern software development practices.
Experience working with machine learning, generative AI, large language models, or information retrieval systems.
Understanding of vector databases, search technologies, embeddings, or retrieval-augmented generation (RAG) concepts.
Experience developing scalable services on public cloud platforms such as Azure, AWS, or Google Cloud.
Familiarity with REST APIs, distributed systems, and cloud-native architectures.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and collaboration abilities.
Preferred Qualifications
Experience with LLM orchestration frameworks and agentic AI systems.
Familiarity with Azure AI Search, Azure OpenAI, or comparable AI services.
Experience with evaluation frameworks, experimentation, and A/B testing methodologies.
Knowledge of containerization and orchestration technologies such as Docker and Kubernetes.
Experience with knowledge graphs, semantic search, or recommendation systems.
Exposure to MLOps, model deployment, and production AI systems.
Experience working in developer tools, enterprise software, or technical documentation environments.