We're seeking a highly motivated Senior Software Engineer to join a scrappy team dedicated to the continued development of our internal AI ecosystem, including tooling for autonomous coding and agentic automation.
\nAs the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.
\nTo succeed on this team you will need to be curious, an excellent communicator, of a strong product mindset, be able to go from idea to implementation, and take ownership and pride in your work.
\nPropose, prototype, and deploy LLM-based agentic systems that help solve real-world problems, leveraging the latest state-of-the-art techniques in the field.
\nWork cross-functionally with different business lines across Anduril to help discover and scope new solutions.
\nDevelop and maintain data pipelines, feature engineering workflows, and model-serving components that support applied AI use cases across the yard.
\nLearn and evangelize. You will be an expert on current AI technologies and trends (and their practical applications).
\nEligible to obtain and maintain an active U.S. Secret security clearance.
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\nThis role goes beyond building models; it's about designing agentic systems, AI-assisted workflows, and data-driven decision engines that help the company scale faster than headcount.
\nYou will be at the forefront of developing the next generation of autonomous systems that power both customer-facing products and internal operations, from optimizing payment experiences to accelerating development, testing, troubleshooting, and product creation.
\nResponsibilities:
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\nDesign autonomous AI systems that can execute technical analysis, testing, troubleshooting, and decision-making at scale.
\nDevelop AI-driven tools that create measurable business impact, improving efficiency, accelerating innovation, and driving revenue growth.
\nOperational Intelligence & Scalability:
\nIdentify areas across Yuno where AI can generate efficiency gains, reducing manual work, optimizing processes, and enabling smarter operations.
\nBuild AI systems that enable Yuno to scale without exponential growth in headcount, thereby creating sustainable productivity and organizational intelligence.
\nData & Model Optimization:
\nLead fine-tuning and contextual optimization of AI models using Yuno's proprietary data.
\nContinuously refine performance through structured feedback loops, observability metrics, and user interaction data.
\nEnsure adherence to privacy, compliance, and ethical AI principles in all model development.
\nCross-Functional Collaboration & Innovation:
\nWork closely with data, product, and infrastructure teams to define the long-term AI roadmap for Yuno.
\nExperiment with emerging AI technologies to identify new capabilities that can drive differentiation and strategic advantage.
\nContribute to a culture of experimentation, rapid iteration, and continuous learning across the AI function.
\nThe skills you need:
\n5+ years of professional experience in AI/ML development, with at least 2 years focused on LLMs, RAG, or agentic systems.
\nStrong engineering and product mindset, capable of balancing technical depth with strategic impact.
\nExceptional communication and collaboration skills to work across product, engineering, and data functions.
\nPassion for pushing the boundaries of applied AI and creating systems that drive real business transformation.
\nWilling to work from the Hyderabad office.
\nMinimum Qualifications:
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\nAI Agents & Multi-Agent Systems: Hands-on experience with Crew.ai, LangChain, LangGraph, or similar frameworks to build orchestrated agentic workflows.
\nFine-Tuning & Context Engineering: Expertise in supervised fine-tuning (SFT), LoRA, or custom dataset adaptation for domain-specific tasks.
\nProgramming & Frameworks: Proficiency in Python, GO, and AI/ML libraries such as PyTorch, TensorFlow, or JAX.
\nAI Infrastructure: Experience designing scalable, production-ready AI systems in AWS, GCP, or Azure, with a deep understanding of vector databases, model serving, and inference optimization.
\nObservability & Monitoring: Familiarity with LangSmith, LangFuse, or equivalent tools for tracking, debugging, and evaluating LLM performance.
\nAPI Integration: Expertise in integrating AI systems with RESTful APIs and internal platforms to create seamless, usable products.
\nPreferred Qualifications:
\nExperience using LlamaIndex, Hugging Face, or similar open-source frameworks.
\nStrong understanding of context optimization, embedding strategies, and knowledge retrieval.
\nFamiliarity with MLOps, CI/CD pipelines, and production deployment best practices.
\nPrior experience in fintech, payments, or other data-intensive and regulated industries.
\nAnalytical rigor and ability to translate business objectives into measurable AI outcomes.
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\nInstrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.
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