Sr. Software Engineer - Analytics

hatch I.T. is partnering with Babel Street to find a Sr. Software Engineer - Analytics. Please see details below:

About the Role

Babel Street is looking for a Senior Software Engineer to join their Analytics Group. This is a high-impact Individual Contributor role for a "builder" who wants to create the next generation of architecture and components for their analytics platform. You will work at the intersection of NLP algorithms, high-scale search engines, and data science techniques, focusing specifically on evolving their record matching functionality.  

While this is an execution-focused role today, we are looking for a technical expert who wants to master a critical domain and has the drive to grow into a leadership position as their platform expands. You will help identify future technology directions and help us create the "next wave" of software for record matching.   

About the Company

Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.  The actionable insights we deliver safeguard lives and protect critical assets around the world.  Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.

What you will do:

Build and Polish: Create new architecture and components for the analytics platform, specifically driving the evolution of record matching.
Drive Technical Direction: Research and prototype new technologies to improve platform performance and define the future technical path for your components.
Own Your Domain: Serve as the primary technical expert for key components, working closely with Product Management to identify and implement critical software improvements.
Mentor and Collaborate: Raise the bar for the team by mentoring junior engineers and participating in agile sprint and release planning.
Ship Scalable Systems: Design and deliver robust APIs and scalable architectures that integrate seamlessly into our broader AI-native platform.  

What you will bring:

Required:

6+ years of experience in professional Java development.

Proven expertise in designing scalable systems and robust APIs.

Deep Search Internals: A strong understanding of Elasticsearch internals, including performance tuning and data modeling.

Growth Mindset: Strong communication and technical skills, with a passion for designing, building, and polishing innovative applications.

Educational Foundation: Bachelor's degree in technical field.  

Preferred (Nice to Have):

Experience with computational linguistics or NLP.

Hands-on experience with Kubernetes.

Experience securing APIs and systems (auth, roles, and secrets management).  

What success looks like:

Month 1–2: Ramp up on the analytics stack and record matching architecture; contribute your first set of improvements to the production environment.
Month 3–4: Take full ownership of a specific component or feature improvement, leading to the design and technical execution.
Month 5–6: Deliver a measurable improvement to record matching quality or Elasticsearch performance and begin identifying the "next wave" of technology for the analytics group. 

Why this role matters:

The record matching functionality is where Babel Street’s signals become usable intelligence. By reconciling complex data points across disparate sources, your work ensures their customers can move from signal to insight with the highest level of trust.   

Do you care about provenance, explainability, and trust?   

When a match decision affects whether someone gets onboarded, sanctioned, or investigated, "the model said so" is not good enough. You'll build systems where every match is defensible, auditable, and tunable, a rare luxury in modern ML-heavy stacks.  

Do you speak multiple languages and want to have a chance to use that in your day-to-day activities?   

Since their platform is multilingual and can match records across languages, your linguistic insights can directly inform how we build and polish the NLP and computational linguistics components that make their record matching world-class