The AI Engineer will be responsible for designing, building, deploying, certifying, and maintaining production-grade generative AI and agentic business and technology solutions.
Key Responsibilities
- Design, create, and implement reusable AI frameworks, prompt templates, reference architecture, and reference architectures to accelerate AI solution delivery across teams.
- Lead the full stack end-to-end development of custom AI solutions leveraging knowledge of MLOps, context management, and CICD practices to orchestrate AI agents and technology (e.g., Copilot AI, Snowflake AI, GitHub AI, AWS Bedrock, etc).
- Collaborate with cloud, data and security architecture teams to build secure, extensible solutions
- 10 years of overall experience in software engineering, data science, or related technical roles, with strong proficiency in coding, business and system design, and production deployment.
- A minimum of 1-2 years of hands-on experience building and deploying systems, preferably generative AI solutions, in enterprise environments
- Bachelor’s degree in Artificial Intelligence, Data Science, or related field or equivalent work experience
- Industry certification or eligibility preferred
- Proficient in backend development using AI algorithms. Python, Java, Shell, Linux or Node.js, MCP, APIs, knowledge graphs, vector databases, & data structures
- Demonstrated knowledge of MLOps, model lifecycle, and (CI/CD) practices.
- Designed and implemented full-stack AI solutions using modern MLOps and AI frameworks (e.g RAG) and platforms such as GitHub Agent, Snowflake Agents, Copilot Studio and AWS Bedrock.
- Created reusable frameworks, prompt templates, and reference architectures to accelerate AI solution delivery across teams.
- Knowledge of data query, analysis, and scanning tools and techniques
- Strong interpersonal, written and oral communication, and analytical skills
- Ability to manage multiple priorities, work independently, coordinate work assignments with management throughout the organization and reliably meet commitments
- Strong aptitude for technology and an ability to learn quickly
About Techstra Solutions
Techstra Solutions is a certified woman-owned (WBENC) management consulting firm specializing in strategy, technology, and implementation services for large organizations undergoing digital and talent transformation. Our experienced team partners with clients to co-create innovative solutions in applications, data, AI, and automation that accelerate measurable, sustainable change. From advisory consulting through technical execution, we are dedicated to driving world-class business solutions that fit your strategic requirements and deliver results. For more information: www.techstrasolutions.com
Skills Required
- 10 years of experience in software engineering, data science, or related technical roles
- 1-2 years of hands-on experience building and deploying generative AI solutions in enterprise environments
- Bachelor's degree in Artificial Intelligence, Data Science, or related field or equivalent work experience
- Proficient in backend development using AI algorithms, with experience in Python, Java, Shell, Linux, or Node.js
- Demonstrated knowledge of MLOps and CI/CD practices
- Designed and implemented full-stack AI solutions
- Strong interpersonal, written and oral communication, and analytical skills
What We Do
Techstra Solutions is a certified woman-owned consulting firm that provides strategy, technology and implementation support to large organizations undergoing digital and talent transformation. The rapid pace of technology innovation required to remain competitive, juxtaposed with the slow rate of change in many organizations, causes most to struggle. To be successful companies must drive new ways of working including the use of technology/analytics and new skillsets (hard/soft) deep into their culture so that they are able to rapidly and continuously react to change. They must also apply new approaches that empower their employees, ensuring its sustainability. At Techstra Solutions we focus on four key areas, otherwise known as the 4 A’s: Automation (Robotic Process Automation (RPA)/Intelligent Automation), Analytics (Reporting/Analytics/AI/ML), Application Modernization (Cloud, Mobility, etc), and Agile-based solutions (DevOps).
