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

Robust 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 [email protected] · (phone hidden)

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

📌 Lead Engineer (Jaipur)
🏢 Aignosis
📍 Jaipur