Engineering Matching Specialist (focus in GenAI and AI/ML roles)

About the role:

Matching is about finding exceptional talent and connecting them with the perfect client. Our team of experts can quickly identify the specific requirements of our clients, and we work closely with them to develop a customized recruitment strategy that meets their unique needs. We take the time to understand the specific skills and attributes required for each role and use our industry knowledge and experience to identify and attract the best talent.

Exceptional Leadership:
As an Andelan, you’ll serve as a role model for the rest of the company; you do not need to manage people to be a leader at Andela! Think about the feedback your peers typically give you – if it usually sounds like the below, we want to hear from you.

• Low ego, low drama: You share credit, take blame. You like being wrong because it means someone else had an even better idea.

• One team mentality: You break silos across teams. You put the company and mission first above your team alone.

• Great listener, hungry for feedback: You’re always seeking to improve – our product, our business, yourself. You solicit diverse opinions and deeply listen.

• Owner, not renter: You see a problem, you fix it or find someone who will. The buck stops with you.

• Team-player: You roll up your sleeves and get scrappy. You do this by proactively collaborating with your team while actively engaging in important details that matter.

• Business problem solver: You’re not just a functional expert; you consistently get praise for approaching your function through the lens of solving business problems.

Responsibilities:

Technical Talent Advisory & Evaluation

• Perform in-depth analysis of engineering resumes and portfolios with a strong lens on software architectures, tech stacks, and system design approaches. Evaluate candidates’ real-world coding experience, scalability considerations, and project relevance against client requirements.

Engineering Capability Assessments

• Lead structured technical screenings and scenario-based interviews to probe problem-solving skills, depth of systems knowledge, and ability to apply engineering principles. Assess strengths across SDLC stages, from architecture through deployment and operations.

Strategic Client Advisory

• Advise CTOs, VPs of Engineering, and Product leaders on engineering talent strategy. Translate project requirements and product roadmaps into talent specifications, guiding clients on the types of engineers and skillsets required to scale effectively. Operate as a strategic engineering partner.

Technical Talent Pipeline Development

• Curate and maintain a network of high-caliber engineers, staying ahead of industry shifts in cloud infrastructure, distributed systems, AI/ML, DevOps, and modern frameworks. Proactively surface candidates who align with emerging client needs.

Stakeholder & Team Alignment

• Collaborate with engineering leadership to ensure candidates align not only on technical ability but also on team practices, delivery models, and long-term architectural direction.

Engineering Career Guidance

• Build trusted relationships with engineers, providing technical career guidance and mapping their expertise to market demand. Position yourself as a long-term advisor helping them navigate opportunities in modern engineering landscapes.

Continuous Technical Depth

• ​Remain current with advancements in cloud platforms, container orchestration, data engineering, AI/ML stacks, and secure development practices—translating this knowledge into sharper evaluation and client advisory.

Qualifications:

• Degree or equivalent qualification in an IT-related field, such as Computer Science, Information Technology, or Software Engineering.

• Proven experience working with Sales Teams or in a Sales/pre-sales-facing role, demonstrating an understanding of the sales process and the ability to work collaboratively with sales professionals.

• Data Engineering/Science/Generative AI Transition: A demonstrated track record of transitioning from software engineering to data engineering or data science. This could be evidenced by relevant work experience, personal projects, or certifications.

• Data Expertise: At least 2 years of experience in data-related roles, with a strong understanding of at least one of the following:

• Data Engineering: Building and maintaining data pipelines, ETL/ELT processes, and working with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).

• Generative AI (GenAI): Experience with large language models (LLMs), prompt engineering, and building applications using GenAI technologies.

• AI/ML: A solid understanding of Machine Learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

• Matching Acumen: The ability to accurately assess the technical skills and experience of candidates for Data Engineering, GenAI, and AI/ML roles. This includes understanding the nuances of different data-related technologies and how they apply to specific client needs.

• Experience leading teams, including managing and motivating team members, setting goals, and ensuring successful project outcomes.

• Demonstrated ability to work remotely, including strong communication skills and the ability to collaborate effectively with team members in different locations.

• Previous experience working in a startup environment, including a willingness to be flexible and adaptable to changing priorities and requirements.

• Experience in a multicultural environment, with an ability to work effectively with team members from diverse backgrounds and cultures.

• Ability to overlap 5 hours with EST (9AM - 2PM EST)

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