Lead Engineer

Lead Engineer - Healthcare Ecosystem Platform software & Computer Vision AI
Aignosis Artificial Intelligence Private Limited
Location: Jaipur, Rajasthan (On-site) · Experience: 4–5+ years, incl. 1–2+ in technical leadership
Qualification: B.E. / B.Tech / MCA — CS, IT, or related · Type: Full-time
CTC: Negotiable, based on experience
About Us
Aignosis is an AI HealthTech company working on early screening and detection in child development. Our platform combines computer vision, behavioural analysis and AI-driven reporting to identify signs of neuro-developmental delay early enough for intervention to matter. We deploy with schools, primary health centres, hospitals and government bodies across India.
The Role
We are building a vertically integrated ecosystem platform, not a single model or a single app. This role owns its technical architecture end to end - from Low-Level Design through systems architecture - while staying hands-on with the AI pipelines at its core. You will work directly with the founding and clinical teams, and build the engineering team around you.
What You'll Own
Systems architecture full platform design: service decomposition, interface and data contracts, HLD and LLD, spanning clinician, parent, school and government-facing surfaces.
AI pipelines - data ingestion → inference → post-processing → serving. Model development, optimisation, deployment and production monitoring, including drift detection and retraining as we scale from pilot camps to state-wide deployment.
Engineering practice and team coding standards, review culture, CI/CD and MLOps discipline. Mentoring a growing team, and translating clinical problems into shippable software without compromising the accuracy and safety a healthcare product demands.
Required Experience
Architecture
HLD, LLD, service decomposition, interface and data contracts, with design ownership defended in review
Platforms rather than single services - shared identity, event backbone, versioned internal APIs
Multi-modal data architecture: video, audio, questionnaires, longitudinal clinical records, with dataset versioning and lineage
Non-functional design: latency budgets on inference paths, multi-tenancy, observability, disaster recovery
Data, Access Control & Security
Strong DBMS fundamentals - schema design, indexing and query performance, transactions, and knowing when a non-relational store is the right call
Permission modelling from first principles: Role- and Attribute-Based Access Control (RBAC/ABAC), least-privilege defaults, tenant isolation, row- and field-level access across clinician, parent, school and government roles
Application security: encryption at rest and in transit, secrets and key management, secure API design, threat modelling, dependency hygiene
Able to set these standards for a team and enforce them in review, so the platform is compliant by construction rather than retrofitted before an audit
Computer Vision & AI
Strong PyTorch, TensorFlow and OpenCV
Object detection (YOLO, Faster R-CNN), segmentation, OCR or tracking
LLM-based solutions (RAG pipelines, LangChain or similar) integrated into CV-driven workflows
Deployment & Performance
APIs (FastAPI/Flask), Docker, Kubernetes, model registries, monitoring
GPU acceleration - CUDA, TensorRT, ONNX Runtime - and scaling inference for production load
Strong Python; C++/CUDA a plus
Healthcare context
Interoperability: FHIR, HL7, DICOM, ABDM (Ayushman Bharat Digital Mission)
Compliance-by-design: IEC 62304, audit trails, consent management, DPDP Act 2023
A default-to-privacy mindset when working with children's data
Leadership
1–2+ years leading engineers, with a track record of growing them
Able to explain technical trade-offs clearly to non-technical founders and clinical stakeholders
Balances depth against delivery timelines
Bonus: Google Cloud Platform (GCP) experience at scale - GKE, Vertex AI, BigQuery, IAM. Regulated-domain background (health, fintech, safety-critical) strongly preferred.
Why Join
Own the core technology behind a screening product that changes early-intervention outcomes for children
A genuinely vast problem space - multi-modal perception, behavioural inference, clinical validity and platform scale, all unsolved and all interacting
Hard real-world engineering at the intersection of CV and generative AI, not a synthetic benchmark
Deployment at population scale through schools, primary health centres and government programmes — reaching children who would otherwise never be screened
Direct visibility to the founding team, and the chance to build the engineering org as we scale
How to Apply
Email jobs@aignosis.in · 9261201154
Please include:
A CV project you took from prototype to production - and what broke along the way
Any GenAI/LLM integration into an existing product
The largest team you've directly led, and for how long
Notice period and expected CTC

Work arrangement
No