Grade Level (for internal use):
03
Who We Are
Kensho is a 120-person AI and machine learning company within S&P Global. With expertise in Machine Learning and data discovery, we develop and deploy novel solutions for S&P Global and its customers worldwide. Our solutions help businesses harness the power of data and Artificial Intelligence to innovate and drive progress. Kensho's solutions and research focus on speech recognition, entity linking, document extraction, automated database linking, text classification, natural language processing, and more.
Are you looking to solve hard problems and enjoy working with teammates with diverse perspectives? If so, we would love to help you excel here at Kensho.
About The Team Kenshos Applications group develops the web apps and APIs that deliver Kenshos AI capabilities to our customers. Our teams are small, product-focused, and intent on shipping high-quality code that best leverages our efforts. Were collegial, humble, and inquisitive, and we delight in learning from teammates with backgrounds, skills, and interests different from our own.
Kensho Link team, within the Applications Department, is a machine learning service that allows users to map entities in their datasets with unique entities drawn from S&P Globals world-class company database with precision and speed. Link started as an internal Kensho project to help S&P Global Market Intelligence Team to integrate datasets more quickly into their platform. It uses ML based algorithms trained to return high quality links, even when the data inputs are incomplete or contain errors. In simple words, Kenshos Link product helps in connecting the disconnected information about a company at one place and it does so with scale. Link leverages a variety of NLP and ML techniques to process and link millions of company entities in hours.
About The Role As a Senior Backend Engineer you will develop reliable, secure, and performant APIs that apply Kenshos AI capabilities to specific customer workflows. You will collaborate with colleagues from Product, Machine Learning, Infrastructure, and Design, as well as with other engineers within Applications. You have a demonstrated capacity for depth, and are comfortable working with a broad range of technologies. Your verbal and written communication is proactive, efficient, and inclusive of your geographically-distributed colleagues. You are a thoughtful, deliberate technologist and share your knowledge generously.
Equivalent to Grade 11 Role (Internal)
You will:
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Design, develop, test, document, deploy, maintain, and improve software
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Manage individual project priorities, deadlines, and deliverables
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Work with key stakeholders to develop system architectures, API specifications, implementation requirements, and complexity estimates
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Test assumptions through instrumentation and prototyping
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Promote ongoing technical development through code reviews, knowledge sharing, and mentorship
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Optimize Application Scaling : Efficiently scale ML applications to maximize compute resource utilization and meet high customer demand.
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Address Technical Debt: Proactively identify and propose solutions to reduce technical debt within the tech stack.
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Enhance User Experiences : Collaborate with Product and Design teams to develop ML-based solutions that enhance user experiences and align with business goals.
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Ensure API security and data privacy by implementing best practices and compliance measures.
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Monitor and analyze API performance and reliability, making data-driven decisions to improve system health.
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Contribute to architectural discussions and decisions, ensuring scalability, maintainability, and performance of the backend systems.
Qualifications
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At least 5+ years of direct experience developing customer-facing APIs within a team
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Thoughtful and efficient communication skills (both verbal and written)
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Experience developing RESTful APIs using a variety of tools
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Experience turning abstract business requirements into concrete technical plans
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Experience working across many stages of the software development lifecycle
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Sound reasoning about the behavior and performance of loosely-coupled systems
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Proficiency with algorithms (including time and space complexity analysis), data structures, and software architecture
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At least one domain of demonstrable technical depth
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Familiarity with CI/CD practices and tools to streamline deployment processes.
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Experience with containerization technologies for application deployment and orchestration.
Technologies We Love -
Python, Django, FastAPI
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mypy, OpenAPI
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RabbitMQ, Celery, Distributed messaging system
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OpenSearch, PostgreSQL, Redis
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Git, Jsonnet, Jenkins, Containerization technology , Container orchestration platform
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Airflow, AWS, Terraform
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Grafana, Prometheus
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ML Libraries: PyTorch, Scikit-learn, Pandas
