{"id":675153,"url":"https://alion.io/job/niural-ai-software-engineer-applied-ai","title":"Software Engineer - Applied AI","company":{"id":997,"name":"Niural AI","domain":"niural.com","url":"https://alion.io/company/niural-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":9,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":84,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lalitpur, Nepal"],"countries":["NP"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Context Engineering","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Langfuse","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenSearch","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Caching","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Structured Outputs","optional":false},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Fine-tuning","optional":true},{"name":"JavaScript","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LoRA","optional":true},{"name":"Model Distillation","optional":true},{"name":"Next.js","optional":true},{"name":"OCR","optional":true},{"name":"PEFT","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Pydantic AI","optional":true},{"name":"React.js","optional":true},{"name":"Synthetic Data","optional":true},{"name":"Tailwind CSS","optional":true},{"name":"Transformers","optional":true},{"name":"TypeScript","optional":true},{"name":"Vite","optional":true}],"status":"live","first_seen_at":"2026-08-31T02:57:51Z","employer_posted_date":"2026-08-31","last_verified_at":"2026-11-02T06:52:53Z","board_verified":true,"closed_at":null,"days_open":63,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":63},"description":"About Niural\nNiural is the AI-native platform that unifies payroll, compliance, HR, and financial operations into a single platform, enabling companies to hire, pay, and manage teams across 150+ countries with speed, accuracy, and intelligence. Backed by Marathon, M13, and Inspired Capital, Niural is redefining the future of work and intelligent finance.\nWhy Niural?\nIf you are a person who was drawn into tech through the promise of creating cutting-edge tools for a more exciting future, but find yourself jaded with the fact that the world's smartest engineers, and the most capable models ever built, are spending their lives optimizing how frequently we click on ads, this is your opportunity to change that.\nWe’re building a future that changes the way companies participate in the new era of the Internet and create truly global products as they participate in a digital economy. If you want to work with an aggressively ambitious team, put AI agents in charge of work that has never been automated before, and build the system of record companies used to hire, pay, and manage people across borders, moving billions of dollars in the process, help us build the future of work and intelligent finance.\nAbout the Job\nWe are hiring a Software Engineer, Applied AI to build the intelligence layer of the Niural platform. You will work on EMMA, our AI orchestration system, shipping agent workflows, retrieval pipelines, and document understanding systems that operate directly on payroll, tax, and compliance data. This is not a research role, and it is not a chatbot bolted onto a SaaS product. The systems you build take real actions on money movement and statutory filings, where “usually right” is a defect. You should have strong Python skills and hands-on production experience with LLM systems: retrieval-augmented generation, tool calling, structured output, and evaluation. We’re looking for someone who treats model behavior as an engineering problem, measures before shipping, and wants to own features end to end.\nResponsibilities\nDesign, build, and ship production LLM features including agent workflows, tool and function calling, MCP servers, and retrieval-augmented generation pipelines.\n\nBuild retrieval systems over statutory guidance, tax authority publications, contracts, and employee handbooks, owning chunking strategy, embedding selection, hybrid search, reranking, and retrieval quality end to end.\n\nBuild structured extraction pipelines for payroll and compliance documents such as paystubs, statutory filings, and PDFs, including schema enforcement, validation, and repair loops.\n\nDefine and maintain evaluation infrastructure: golden datasets, regression suites in CI, LLM-as-judge calibration, and accuracy and hallucination rate tracked as first-class metrics.\n\nOptimize latency and cost per task through model routing, prompt and semantic caching, batching, and context window budgeting.\n\nImplement safety and correctness controls including PII detection and redaction, prompt injection defense, grounded citations, confidence thresholds, and escalation to human reviewers.\n\nInstrument and monitor AI systems in production using tracing and observability tooling, and debug model behavior with the same rigor applied to application code.\n\nCollaborate with payroll, tax, and compliance experts to translate regulatory requirements into system behavior, and with product and design to ship user-facing AI features.\n\nStay abreast of a fast-moving field and bring back what is actually useful, with a bias toward measurable improvement over novelty.\n\nRequirements\n3 plus years of professional software engineering experience, including recent production experience shipping LLM-backed features to real users.\n\nStrong Python skills and comfort in service-oriented codebases: APIs, queues, background workers, and observability.\n\nHands-on experience with retrieval-augmented generation: embedding models, vector stores (pgvector, OpenSearch, Pinecone, or equivalent), hybrid search, reranking, and query rewriting.\n\nHands-on experience with agent architectures: tool and function calling, multi-step planning, state and memory, error recovery, and human-in-the-loop checkpoints.\n\nExperience with structured output: JSON schema enforcement, constrained decoding, validation and repair.\n\nExperience designing and running LLM evaluations and regression testing, not just eyeballing outputs.\n\nWorking knowledge of prompt and context engineering: versioning, few-shot selection, context budgeting, and prompt caching.\n\nExperience with LLM observability and tracing tooling such as Langfuse, LangSmith, or OpenTelemetry.\n\nSound judgment on where a model belongs and where deterministic code belongs in a regulated, accuracy-critical domain.\n\nClear written communication and a habit of documenting technical decisions.\n\nNice to Have\nAWS Bedrock or comparable multi-provider production experience.\n\nMCP server design and deployment, including tool schema design, authentication, and scoping.\n\nAgent orchestration frameworks such as LangGraph, LlamaIndex, or Pydantic AI.\n\nFine-tuning or distillation of small models for narrow, high-volume tasks (LoRA/PEFT).\n\nVision-language models or OCR pipelines for document understanding.\n\nSynthetic data generation for evaluation or training.\n\nKnowledge graph or ontology-backed retrieval.\n\nReact and TypeScript (Next.js, Vite, Tailwind) for shipping your own UI when needed.\n\nFintech, payroll, tax, HR tech, or another regulated domain.\n\nOpen-source contributions to the AI tooling ecosystem.\n\nWhat we offer\nCompetitive salary package designed to reward your expertise and contributions.\n\nAccess to continuous learning and career advancement programs.\n\nOpportunities for mentorship and coaching to help you grow in your career.\n\nSupportive and collaborative work environment where ideas are valued and teamwork is encouraged.\n\nComplimentary snacks and lunch provided to keep you energized throughout the shift.\n\nLatest MacBook Pro and a high-performance monitor will be provided to boost your productivity.\n\nWe’ve partnered with select universities in the US to provide “fast track” admissions to star performers who may want to pursue their Masters in CS in the US.\n\nHigh performers will be sponsored for L1 visas as well as immigrant visas (Green Card) to the US.","description_format":"text","description_chars":6329,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Apple Macbook","Continuous learning"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial 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