Backend Engineer - AI-Powered Search & Applications (Remote | Immediate Joiners)

This a Full Remote job, the offer is available from: Indiana (USA) Join Proximity Works, one of the world’s most ambitious AI technology companies, shaping the future of Sports, Media, and Entertainment. Since 2019, Proximity Works has created and scaled AI-driven products used by 697 million daily users, generating $73.5 billion in enterprise value for our partners. Headquartered in San Francisco with offices in Los Angeles, Dubai, Mumbai, and Bangalore, we help global brands discover high-impact AI use cases, build transformative tech stacks, and scale to hundreds of millions of users. If you’re excited about building high-performance backend systems at the frontier of AI, this role will give you the opportunity to make global impact. Role Summary We are seeking a Backend Engineer to design, build, and scale resilient microservices and APIs that power next-generation AI products. You will partner closely with ML engineers and data scientists to productionize LLMs, RAG pipelines, and multimodal models, ensuring inference is fast, cost-efficient, and production-grade. This is a hands-on role for someone passionate about distributed systems, performance optimization, and bringing cutting-edge AI to millions of users. What You’ll Do

• Design and build scalable microservices that power Proximity’s AI-driven search and discovery stack.
• Develop backend services and APIs to support LLM-powered applications.

Collaborate with ML engineers and data scientists to integrate RAG pipelines, multimodal models, and inference workloads into production.

• Optimize inference pipelines for latency, throughput, and cost efficiency (e.g., batching, caching, token budgeting).
• Own end-to-end delivery of complex backend projects, from design to deployment and monitoring.
• Write high-quality, maintainable code with rigorous testing and fault-tolerant practices.
• Drive operational excellence through performance tuning, incident response, and root cause analysis.
• Work cross-functionally with Product Managers, Data Scientists, and global engineering teams to translate business needs into scalable technical solutions.

What Success Looks Like

• Robust, resilient backend systems powering AI-driven applications for Proximity’s global partners.
• Consistent reduction in inference latency and infrastructure costs.
• High availability and fault tolerance across production services.
• Rapid, collaborative feature delivery with product and ML teams.
• Clear documentation and monitoring practices that ensure operational smoothness.

Requirements

What You’ll Need

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 4–6 years of backend development experience, ideally with exposure to AI or large-scale data systems.
• Proficiency in Java, Golang, or Python with strong coding and system design fundamentals.
• Experience designing and scaling distributed systems at production scale.
• Exposure to LLM inference setups (e.g., vLLM, Hugging Face Inference, Triton).
• Strong debugging, profiling, and performance tuning skills for latency-sensitive applications.
• Knowledge of storage systems, query optimization, and caching strategies.
• Hands-on experience with AWS (preferred), Kafka, and CI/CD pipelines.
• Ability to work autonomously and deliver in fast-paced environments.
• Passion for mentoring engineers and leading by example.
• Curiosity about ad-tech and search systems, and how to optimize them for user and business outcomes.

Success Traits Builder’s mindset · High ownership · Analytical clarity · Collaborative spirit · Global mindset · Growth orientation

Benefits

Why Join Proximity Works

• Work directly on frontier AI problems with some of the world’s largest sports, media, and entertainment brands.
• Be part of a global-first, high-performance engineering culture.
• Competitive compensation aligned with global markets, with remote-first flexibility.
• Annual global off-sites with Proxonauts from San Francisco, Dubai, India, and beyond.
• High autonomy, direct accountability, and the opportunity to ship AI systems at scale.

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