Technology

Software Engineer (AI Engineering) - Only W2

Info Dinamica IncAK🇺🇸United StatesPosted Sep 18, 2026

Quick Overview

Seniority

Mid Senior

Work mode

Hybrid

Location

AK, United States

Posted

18 hours ago

MicroservicesSQLAWSMachine LearningAgileAzureDatabricksGenerative AIGitGoogle CloudJavaJavaScriptPythonREST

Role: Software Engineer I (A2) AI Engineering

Remote (US)

Job Type: W2 Contract

Duration: 6+ months

Role Overview:

We are seeking a motivated Software Engineer I (A2) AI Engineering to support the development and implementation of AI-powered applications and engineering solutions. This role is ideal for engineers with 3-5 years of software development experience and an interest in modern AI technologies, including Large Language Models (LLMs), Generative AI, Retrieval Augmented Generation (RAG), GitHub Copilot, Claude, Databricks, and cloud-based platforms.
You will work closely with senior engineers, architects, product managers, and data teams to build scalable and secure AI solutions that improve developer productivity, business processes, and customer experiences.

Key Responsibilities:

AI Application Development

Develop and enhance AI-powered applications using LLMs, RAG frameworks, and modern AI services.
Build and integrate APIs, AI workflows, and automation solutions under the guidance of senior team members.
Support implementation of AI use cases using GitHub Copilot, Claude, Azure AI Services, OpenAI models, and Databricks.
Participate in evaluating and testing new AI tools and technologies.
Assist in developing prompt engineering and retrieval-based solutions for business applications.

Software Engineering

Design, develop, test, and maintain high-quality software applications and services.
Contribute to all phases of the Software Development Lifecycle (SDLC), including development, testing, deployment, and production support.
Follow engineering best practices for code quality, security, performance, and maintainability.
Develop REST APIs, microservices, and cloud-native applications.
Participate in code reviews and continuously improve development practices.

Data & AI Engineering

Support development of data pipelines and AI-ready datasets using Databricks, Spark, SQL, and related technologies.
Assist in implementing vector search, embeddings, and retrieval solutions for AI applications.
Monitor and troubleshoot AI application performance, reliability, and operational issues.
Analyze data and model outputs to improve solution effectiveness and user experience.

Collaboration & Delivery

Work closely with product managers, business stakeholders, data engineers, and senior developers to deliver AI solutions.
Participate in Agile ceremonies, sprint planning, backlog refinement, and team discussions.
Document technical designs, implementation approaches, and operational procedures.
Communicate progress, risks, and challenges effectively within the team.

Security & Responsible AI

Follow Mastercard security, privacy, and Responsible AI guidelines during solution development.
Support testing and validation of AI solutions for accuracy, reliability, and compliance.
Participate in risk assessments and quality reviews as required.

Required:

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
3-5 years of software engineering experience.
Experience with one or more programming languages such as Java, Python, or JavaScript.
Understanding of software development fundamentals, APIs, databases, data structures, and cloud technologies.
Exposure to AI/ML concepts, Generative AI, LLMs, or machine learning solutions.
Experience with Git, CI/CD pipelines, and Agile development methodologies.

Preferred:

Hands-on experience with GitHub Copilot, Claude, OpenAI, Azure AI Services, or similar AI platforms.
Knowledge of RAG architectures, vector databases, embeddings, or prompt engineering.
Experience with Databricks, Spark, SQL, or data engineering tools.
Familiarity with Azure, AWS, or Google Cloud Platform cloud platforms.
Understanding of Responsible AI, security, and data privacy principles.