AION

aion is seeking a backend engineer to advance its Compute and Inference platforms. You will write production-grade Go code, design scalable APIs, and help implement multi-cloud orchestration, resource management, and autoscaling. Collaboration with senior engineers and product teams will shape resilient, end-to-end infrastructure. Join a fast-growing startup building the enterprise AI platform, with opportunities across UI, docs, customer success, and product ops as needed.

About aion Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform. We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters. We're a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we're building the next generation of enterprise AI and we're looking for exceptional people to help us scale. Who You Are You're a solid engineer with 2-4 years of experience building backend systems and platform infrastructure. You write clean, well-abstracted code with proper design patterns and comprehensive test coverage. You're comfortable working on both the Compute Platform (multi-cloud orchestration, resource management) and Inference Platform (model serving, autoscaling) under the guidance of senior engineers and platform leads. You have strong proficiency in Golang and understand how to build maintainable, production-grade distributed systems. You take pride in code quality, enjoy collaborating on low-level designs, and are eager to learn from experienced engineers while contributing meaningfully to critical infrastructure components. You're product-minded, you understand how your technical decisions impact developers using aion's platform and think about the end-to-end user experience. You're a team player comfortable wearing multiple hats one day you're building product features, the next you're joining customer calls to understand their deployment challenges, and the day after you're helping with UI/UX, customer success, documentation and product ops. What You'll Do Platform Development & Implementation Build and maintain platform services across aion's Compute and Inference platforms, working closely with senior engineers and platform leads Implement features for multi-cloud orchestration, resource scheduling, model deployment pipelines, and autoscaling systems Write well-maintained, production-grade code with proper abstractions, design patterns, and comprehensive test coverage Contribute to low-level design (LLD) including service APIs, database schema design, data models, and component interactions Collaborate with senior engineers on high-level design discussions, providing implementation perspectives and feasibility inputs Backend Systems & Distributed Infrastructure Develop RESTful APIs and gRPC services for platform control planes, resource management, and inference serving Design and implement database schemas for storing platform state, resource metadata, billing data, and observability metrics Work with distributed storage systems, message queues (Kafka, RabbitMQ), and databases (PostgreSQL, Redis) to build reliable platform components Build event-driven architectures for asynchronous processing, job scheduling, and platform automation Implement monitoring, logging, and alerting for platform services to ensure production reliability Code Quality & Engineering Excellence Write comprehensive unit tests, integration tests, and end-to-end tests to ensure code reliability Participate in code reviews, providing constructive feedback and learning from senior engineers' perspectives Refactor existing code to improve maintainability, performance, and scalability Document design decisions, API specifications, and operational runbooks for platform services Debug production issues and contribute to incident response and post-mortems Technical Skills & Experience 2-4 years of experience in backend engineering, platform development, or distributed systems Strong proficiency in Golang you write idiomatic Go code with proper error handling, concurrency patterns, and testing Solid understanding of backend systems fundamentals: RESTful APIs, microservices architecture, and API design principles Hands on experience with databases (PostgreSQL, MySQL) including schema design, query optimization, and transactions Familiarity with storage systems (object storage like S3, block storage, distributed file systems) and their use cases Experience working with message queues (Kafka, RabbitMQ, NATS) and event-driven architectures Understanding of distributed systems concepts: consensus, eventual consistency, fault tolerance, and retry mechanisms Experience with containerization (Docker) and basic Kubernetes concepts Knowledge of testing frameworks and practices (unit tests, integration tests, mocking) Familiarity with Git, CI/CD pipelines, and modern development workflows Exposure to cloud platforms (AWS/GCP/Azure) and their core services is a plus Experience with infrastructure-as-code (Terraform) or observability tools (Prometheus, Grafana) is beneficial Bonus/ Good to Have HPC & Cluster Management: Experience handling large-scale HPC clusters using Kubernetes and Slurm for job scheduling, resource allocation, and workload orchestration Data Engineering: Expertise with data pipelines, ETL systems, and large-scale data processing frameworks Systems-Level Programming: Experience with low-level systems programming such as storage systems, Kubernetes operators, OS-level software development, or daemon services (llm-d, system agents) ML Platform Engineering: Experience productionizing ML pipelines, batch job orchestration, model fine-tuning workflows, and Jupyter notebook orchestration systems Enterprise Deployment: Experience platformizing and packaging software for on-premises deployments or customer VPC installations with emphasis on security, compliance, and operational simplicity Preferred Attributes: High ownership, self driven and biased for action. Strong strategic thinking and ability to connect technical decisions to business impact. Excellent communication and mentoring skills. Thrives in ambiguity, fast-paced environments, and early stage startup culture. Why Join aion? Work directly with high pedigree founders shaping technical and product strategy. Build infrastructure powering the future of AI computers globally. Significant ownership and impact with equity reflective of your contributions. Competitive compensation, flexible work options, and wellness benefits

About aion Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform. We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters. We're a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we're building the next generation of enterprise AI and we're looking for exceptional people to help us scale. Who You Are You're a hands-on AI engineer with 3-5+ years of experience building production-grade multimodal AI systems and LLM applications. Your responsibilities mirror those of a hands-on AI startup CTO you work in small teams to own delivery of high-stakes customer projects, embedding directly at client sites to architect, build, and deploy intelligent agent solutions. You're equally comfortable writing production code, presenting technical solutions to C-level executives, and debugging complex AI systems on factory floors or in customer data centers. You've shipped voice agents, video processing systems, or conversational AI to production. You thrive translating ambiguous business requirements into concrete technical solutions that create measurable impact. You're comfortable working across the full AI deployment lifecycle from use case discovery and solution architecture to multimodal agent development, MLOps pipeline implementation, and production optimization. You understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience with voice AI platforms, RAG systems, and LLM orchestration frameworks is highly desirable. You bring exceptional communication skills, customer empathy, and the drive to build AI solutions that transform enterprise operations globally. What You'll Do Customer Engagement & Multimodal Agent Development Work directly at customer sites from factory floors to executive offices conducting discovery workshops and technical assessments to identify high-impact AI opportunities Design and architect end-to-end multimodal agent systems (voice + video + text) that leverage aion's distributed GPU infrastructure and managed services Build production-grade voice AI systems using STT, TTS APIs, and LLMs deployed on aion's platform Develop vision-enabled agents processing real-time video streams using computer vision pipelines on aion's infrastructure Implement sophisticated multi-agent orchestration with(or similar) frameworks like LangChain or LlamaIndex-enabling tool use, memory management, and autonomous task completion Rapidly prototype POCs in 2-4 weeks, coding alongside client teams to validate concepts and iterate based on feedback Optimize for sub-500ms latency, natural conversation flow, turn detection, and interruption handling in real-time systems Integrate agents directly into customer codebases via REST/GraphQL/WebSocket APIs and custom SDKs (Python, TypeScript) Act as trusted technical advisor to customers, shaping AI strategy and guiding roadmap decisions from concept to production Data Strategy & MLOps Infrastructure Design data architectures with efficient processing pipelines and ingestion workflows for training and inference on aion's platform Implement RAG systems with vector databases optimizing embedding strategies, chunk sizes, and retrieval methods Prepare and validate datasets for fine-tuning, evaluation, and synthetic data generation Work with other MLEs, MLOps, SREs to carry out model deployment and productionization Observability, Evaluation & Production Operations Implement LLM and agents observability and monitoring tracking token usage, latency, costs, and quality metrics across deployments on aion's infrastructure Instrument applications to trace LLM calls, retrieval operations, agent actions, and data flows Build evaluation frameworks with offline benchmarks (accuracy, relevance, safety metrics) and online monitoring (user feedback, drift detection) Technical Skills & Experience 3-5+ years of hands-on experience building production AI/ML systems, with 1-2+ years deploying LLM applications to production Multimodal AI expertise practical experience building voice agents, vision systems, or conversational AI serving real users Strong LLM foundations hands-on with modern foundation models including fine-tuning, prompt engineering, and evaluation methodologies Agent framework proficiency production experience with LangChain, LlamaIndex, or similar orchestration frameworks Voice AI platform experience built real-time conversational systems with production STT/TTS integration Proficiency in Python (production-grade, async programming, type hints) and JavaScript/TypeScript (full-stack development) RAG implementation experience built retrieval-augmented generation systems with vector databases MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code Cloud platforms experience with AWS, Azure, or GCP for ML workloads and infrastructure management Exceptional communication ability to explain complex AI concepts clearly to both technical and business stakeholders Customer-facing experience in Solutions Architecture, Technical Account Management, or Pre-Sales Engineering is highly desirable Computer vision experience working with video processing, object detection, or vision-language models is a plus Model fine-tuning practical experience with LoRA/QLoRA, supervised fine-tuning, or RLHF workflows is a plus Inference optimization experience with vLLM, TensorRT-LLM, Triton, or model quantization techniques is desirable Observability tooling practical experience with LLM monitoring, tracing, and evaluation frameworks is a strong plus Familiarity with WebRTC, real-time streaming protocols, and low-latency media processing Preferred Attributes: Founder-level ownership and bias for action. Strong strategic thinking and ability to connect technical decisions to business impact. Excellent communication and mentoring skills. Thrives in ambiguity, fast-paced environments, and early-stage startup culture. Why Join aion? Work directly with high-pedigree founders shaping technical and product strategy. Build infrastructure powering the future of AI compute globally. Significant ownership and impact with equity reflective of your contributions. Competitive compensation, flexible work options, and wellness benefits

aion is seeking a hands-on AI engineer with 3-5+ years of experience building production-grade multimodal AI systems and LLM applications. You will work directly at client sites to architect, build, and deploy intelligent agent solutions that solve real business problems. You will collaborate with customers, design end-to-end pipelines, integrate with REST/GraphQL, and help shape AI strategy from concept to production.

About aion Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform. We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters. We're a fast-growing, VC-backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we're building the next generation of enterprise AI and we're looking for exceptional people to help us scale. Who You Are You're a hands-on AI engineer with 3-5+ years of experience building production-grade multimodal AI systems and LLM applications. Your responsibilities mirror those of a hands-on AI startup CTO you work in small teams to own delivery of high-stakes customer projects, embedding directly at client sites to architect, build, and deploy intelligent agent solutions. You're equally comfortable writing production code, presenting technical solutions to C-level executives, and debugging complex AI systems on factory floors or in customer data centers. You've shipped voice agents, video processing systems, or conversational AI to production. You thrive translating ambiguous business requirements into concrete technical solutions that create measurable impact. You're comfortable working across the full AI deployment lifecycle from use case discovery and solution architecture to multimodal agent development, MLOps pipeline implementation, and production optimization. You understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation. Experience with voice AI platforms, RAG systems, and LLM orchestration frameworks is highly desirable. You bring exceptional communication skills, customer empathy, and the drive to build AI solutions that transform enterprise operations globally. What You'll Do Customer Engagement & Multimodal Agent Development Work directly at customer sites from factory floors to executive offices conducting discovery workshops and technical assessments to identify high-impact AI opportunities Design and architect end-to-end multimodal agent systems (voice + video + text) that leverage aion's distributed GPU infrastructure and managed services Build production-grade voice AI systems using STT, TTS APIs, and LLMs deployed on aion's platform Develop vision-enabled agents processing real-time video streams using computer vision pipelines on aion's infrastructure Implement sophisticated multi-agent orchestration with(or similar) frameworks like LangChain or LlamaIndex-enabling tool use, memory management, and autonomous task completion Rapidly prototype POCs in 2-4 weeks, coding alongside client teams to validate concepts and iterate based on feedback Optimize for sub-500ms latency, natural conversation flow, turn detection, and interruption handling in real-time systems Integrate agents directly into customer codebases via REST/GraphQL/WebSocket APIs and custom SDKs (Python, TypeScript) Act as trusted technical advisor to customers, shaping AI strategy and guiding roadmap decisions from concept to production Data Strategy & MLOps Infrastructure Design data architectures with efficient processing pipelines and ingestion workflows for training and inference on aion's platform Implement RAG systems with vector databases optimizing embedding strategies, chunk sizes, and retrieval methods Prepare and validate datasets for fine-tuning, evaluation, and synthetic data generation Work with other MLEs, MLOps, SREs to carry out model deployment and productionization Observability, Evaluation & Production Operations Implement LLM and agents observability and monitoring tracking token usage, latency, costs, and quality metrics across deployments on aion's infrastructure Instrument applications to trace LLM calls, retrieval operations, agent actions, and data flows Build evaluation frameworks with offline benchmarks (accuracy, relevance, safety metrics) and online monitoring (user feedback, drift detection) Technical Skills & Experience 6-8+ years of hands-on experience building production AI/ML systems, with 3-4+ years deploying LLM applications to production Multimodal AI expertise practical experience building voice agents, vision systems, or conversational AI serving real users Strong LLM foundations hands-on with modern foundation models including fine-tuning, prompt engineering, and evaluation methodologies Agent framework proficiency production experience with LangChain, LlamaIndex, or similar orchestration frameworks Voice AI platform experience built real-time conversational systems with production STT/TTS integration Proficiency in Python (production-grade, async programming, type hints) and JavaScript/TypeScript (full-stack development) RAG implementation experience built retrieval-augmented generation systems with vector databases MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code Cloud platforms experience with AWS, Azure, or GCP for ML workloads and infrastructure management Exceptional communication ability to explain complex AI concepts clearly to both technical and business stakeholders Customer-facing experience in Solutions Architecture, Technical Account Management, or Pre-Sales Engineering is highly desirable Computer vision experience working with video processing, object detection, or vision-language models is a plus Model fine-tuning practical experience with LoRA/QLoRA, supervised fine-tuning, or RLHF workflows is a plus Inference optimization experience with vLLM, TensorRT-LLM, Triton, or model quantization techniques is desirable Observability tooling practical experience with LLM monitoring, tracing, and evaluation frameworks is a strong plus Familiarity with WebRTC, real-time streaming protocols, and low-latency media processing Preferred Attributes: Founder-level ownership and bias for action. Strong strategic thinking and ability to connect technical decisions to business impact. Excellent communication and mentoring skills. Thrives in ambiguity, fast-paced environments, and early-stage startup culture. Why Join aion? Work directly with high-pedigree founders shaping technical and product strategy. Build infrastructure powering the future of AI compute globally. Significant ownership and impact with equity reflective of your contributions. Competitive compensation, flexible work options, and wellness benefits

AION is seeking a hands-on AI engineer with 6-8+ years of experience to join our enterprise AI platform team. You will own delivery of high-stakes customer projects, embedding at client sites to architect, build, and deploy multimodal AI systems and LLM applications. You'll drive end-to-end development from discovery to production, work across voice, vision, and text, and leverage LangChain, LlamaIndex, and modern MLOps on AWS/Azure/GCP to deliver scalable, observable AI solutions at scale.