AI Engineer

Job Title: AI Engineer Company: OnIT Job Category: Machine Learning Roles & Responsibilities: About Onit We're redefining the future of legal operations through the power of AI. Our cutting\-edge platform streamlines enterprise legal management, matter management, spend management and contract lifecycle processes, transforming manual workflows into intelligent, automated solutions. We’re a team of innovators using AI at the core to help legal departments become faster, smarter, and more strategic. As we continue to grow and expand the capabilities of our new AI\-centric platform, we’re looking for bold thinkers and builders who are excited to shape the next chapter of legal tech. If you're energized by meaningful work, love solving complex problems, and want to help modernize how legal teams operate, we’d love to meet you. ### Agentic AI Feature \& Workflow Development * Build and integrate AI\-driven features using LLM APIs (OpenAI / Azure OpenAI, Anthropic, Gemini on Vertex AI) * Design and implement tool\-using agents (structured function calling, schema validation, retries, fallbacks) * Build multi\-agent workflows when appropriate (e.g., planner/worker, reviewer/critic, specialist routing) and know when a simpler architecture is better * Create agentic workflows such as document understanding, extraction, reasoning over evidence, task automation, and multi\-step decision support * Own context engineering end\-to\-end: * dynamic context assembly (retrieval \+ state \+ tool outputs) * context budgeting and compression/summarization * grounding strategies to reduce hallucinations and improve consistency * Implement retrieval\-augmented generation (RAG) and search workflows using off\-the\-shelf vector stores and embedding services ### Evaluation, Quality \& Iteration (Core) * Establish evaluation frameworks for accuracy, reliability, and output quality * Build task\-specific eval suites: golden datasets, adversarial cases, regression tests, and rubric\-based scoring * Set up automated evaluation pipelines and release gates (CI/CD\-friendly) tied to prompt/model/version changes * Define and monitor online metrics (e.g., task success rate, human override rate, safety flags, latency, cost) and run experiments/A\-B tests where appropriate * Use LLM\-as\-judge responsibly: calibrate, validate, and pair with human labels when needed ### Engineering, Integration \& Observability * Develop scalable backend services and APIs that incorporate AI functionality * Integrate AI pipelines into existing cloud, microservices, and event\-driven architectures * Implement observability and analytics for all AI features (tracing, evaluations, prompt versioning, cost tracking) Example tooling: Langfuse (and/or OpenTelemetry\-compatible stacks) * Ensure reliability, uptime, performance, and security of AI services * Build internal tooling for evaluation, testing, prompt/version management, and safe deployment ### Product \& Collaboration * Partner with product managers, designers, the Chief Architect, and domain SMEs to shape AI\-first solutions * Rapidly prototype concepts and iterate based on user feedback and measurable eval results * Translate business problems into well\-structured AI workflows without requiring ML model training * Document system behavior, known failure modes, and operational playbooks ### Governance \& Safety * Implement guardrails, checks, and fallback logic for safe and predictable AI behavior * Help define and follow compliance, privacy, and responsible AI guidelines * Design for safe tool execution (bounded actions, permissions, escalation paths, human\-in the\-loop review ### Core Strengths (Required) * You’ve shipped an LLM/agent system in production and can clearly explain: * the failure modes you discovered * the evals you built to catch regressions * how you improved cost/latency while increasing quality * how you monitored and iterated safely over time * You keep up with industry developments (model releases, frameworks, best practices) and can translate them into pragmatic improvement ### Nice to Have Ship one production agent workflow end\-to\-end with: * tracing \+ observability * an offline eval suite with regression gates * cost/latency targets and monitoring * documented failure modes and fallback path Benefits \& Perks That Support You: Onit offers a comprehensive total rewards package designed to support the whole employee at work and beyond: Health Coverage: Employee and immediate family members. Time Away: Flexible paid time off and 10 company paid holidays annually. Family Support: Exceptional paid leave for birth parents, non\-birth parents, and caregivers. Onit also offers surrogacy and adoption reimbursement.* Income Protection: 100% employer\-paid life and disability insurance.* Additional Coverage Options: Voluntary benefits including hospital indemnity, critical illness, accident*.* Tax\-Advantaged Accounts: Flexi, NPS*. Community Engagement: One paid volunteer day each year to give back to the community. Our Commitment to Applicants We know that not everyone will check every box in a job description. At Onit, we value diversity, inclusion, and authenticity. If you’re excited about this role but your experience doesn’t align perfectly with every qualification, we encourage you to apply. You may be exactly who we’re looking for. Onit ValuesCustomer First \- Customer success is our success. We deliver value, listen, and act on customer needs.Purposeful Innovation \- Innovation fuels our growth. We harness creativity to solve problems and lead with the intentions and expertise.Win as One \- Teamwork is how we win. We are accountable, act with integrity, and communicate openly.Intentional Growth \- Our people are the difference. We create an environment with compelling work, impactful contributions, and career growth. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Work Location: MH, India Availability: Full time

* Experience with cloud platforms (AWS and/or GCP), microservices, and event\-driven systems * Experience with observability stacks (OpenTelemetry, Datadog, Honeycomb) and AI\-specific tooling (e.g., Langfuse, Braintrust, HumanLoop, MLFlow) * Experience with workflow orchestration for long\-running jobs (Temporal, Celery, Airflow) * Experience building enterprise AI features (permissions, auditability, compliance constraints) * Experience with safety/policy layers (PII handling, prompt injection defenses, sandboxed tool execution) ### Why Join Us * Build core AI capabilities that directly impact users and product strategy * Work on cutting\-edge, real\-world agentic systems—focused on applied engineering (no model training required) * High ownership, fast iteration cycles, and strong cross\-functional collaboration * Competitive compensation and opportunities for rapid advancement ### What Your First 90 Days Could Look Like Key Skills: Python, Model Training Salary: Not disclosed