Senior Software Engineer, AdeptID
Talent Matching Software
$182k
Talent matching engine
Be an early applicant
Talent matching engine
21-100 employees
Be an early applicant
$182k
21-100 employees
Company mission
To get more people into better jobs, faster.
Role
Who you are
- 5+ years of software engineering experience with strong Python skills
- Hands-on experience designing and operating production APIs and backend services at scale
- Experience designing asynchronous APIs (queues, events, webhooks, or streaming) and reasoning about concurrency
- Comfortable in a stack like ours: Python on AWS, infrastructure as code using CDK, asynchronous services over SQS, and Postgres (with VectorChord for vector search)
- Fluency with AI-assisted development: building with coding agents and LLM tools is part of your normal workflow
- Strong fundamentals in testing, observability, and debugging across distributed systems
- Nice to have: experience with small language models (SLMs), including fine-tuning, evaluation, or serving them in production
- Nice to have: experience close to AI/ML systems, such as model serving, retrieval, or evaluation harnesses
- Staffing, recruiting, or HR tech experience is a plus
What the job involves
- We are hiring a Senior Software Engineer to build the core software behind our talent matching: the services that search, score and rank candidates and the APIs that deliver matches to some of the largest HR technology organizations in the world, and to our own staffing business
- Data Science owns the matching and language models; you own the production services, serving layer, and APIs that put them to work reliably and at low latency. This is a hands-on role for an engineer who builds with modern AI tooling by default, on a small and growing team
- Design, build, and operate the backend services and APIs that power talent matching in production
- Build asynchronous, event-driven APIs and pipelines that stay fast and reliable under load
- Partner with Data Science to take their matching and language models from prototype to reliable production services
- Use AI-assisted development daily to design, write, test, and review code, and help set our standards for it
- Own quality for what you ship: testing, monitoring, latency, and cost
- Collaborate with Product and Operations to turn real recruiter and candidate needs into shipped features
Our take
Talent identification and acquisition has always been a challenge for HR teams, but the labor shortage is making it more difficult than ever. The founders of AdeptID believe that poor talent matching is a billion-dollar problem, and they’re aiming to address it with its machine-learning-powered API.
While there’s no shortage of talent search and matching platforms, from LinkedIn to Zoho Recruit, AdeptID sets itself apart by providing an API which plugs into existing infrastructure. Another interesting aspect of AdeptID’s approach is how its ML tech focuses on lesser-explored talent avenues, particularly candidates who don’t hold degrees and might otherwise be filtered out in other talent searches.
Having only launched in 2020, AdeptID's bootstrapped first year brought in an encouraging $1 million. Since then, it's been backed by Zeal Capital Partners, and the company has been scaling operations in the last couple of years. It is also a certified B-Corp, and in 2023, partnered with OneTen to improve hiring outcomes for black talent in the US.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Dec 2021
$3.5m
SEED
Total funding: $3.5m
Company HQ
Financial District, Boston, MA
Leadership
Fernando Rodriguez-Villa
(Co-Founder & CEO)Previously a Commercial Lead and Founding Team Member at satellite analytics company TellusLabs (acquired by Indigo). Became Indigo's Director of International Strategy post acquisition. Also worked in Business Development at adaptive learning company Knewton.
Brian DeAngelis
(Co-Founder & Chief Data Scientist)Served as a Data Scientist at Indigo before co-founding AdeptID. Previously worked as an Analyst at Opera Solutions, specializing in Machine Learning and Data Science. Co-founded the Hopewell Hockey Company in 2016.
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