Senior Software Engineer II, Embedded AI
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Key skills for this role
Role Overview
Build and ship production services for government platforms and train the models embedded in those services.
Own defined problems from data preparation and design through development, production deployment, and ongoing operation.
Three positions are open across two rural digital infrastructure programmes.
Most work involves registries, credential and wallet layers, group financial records, synchronization for intermittent connectivity, offline-first clients, and migrations.
Key Skills for This Role
Full Job Posting
The Role
Build and ship production services for government platforms and train the models embedded in those services.
Own defined problems from data preparation and design through development, production deployment, and ongoing operation.
Three positions are open across two rural digital infrastructure programmes.
Most work involves registries, credential and wallet layers, group financial records, synchronization for intermittent connectivity, offline-first clients, and migrations.
Core Job Responsibilities
- Own services and features end to end, including design, data model, build, test, deployment, and monitoring.
- Write backward-compatible APIs and integrations for existing institutional systems.
- Train and ship models through feature engineering, selection, training, evaluation, packaging, and serving.
- Evaluate models using appropriate test sets and metrics, checking leakage and subgroup performance.
- Prepare incomplete and inconsistent institutional data through ingestion, validation, and reconciliation.
- Build for intermittent connectivity, older devices, and failed-action scenarios.
- Monitor errors, latency, drift, override rates, and user abandonment.
- Write regression tests, review code, and maintain a green build.
- Protect personal data with access control, encryption, and audit trails.
- Write documentation for running, extending, and retraining systems.
- Review the work of engineers below this level.
Qualifications and Competencies
- Four or more years building and shipping production software, including personally trained and deployed models.
- Backend engineering experience with APIs, data models, migrations, and production support.
- Production-standard Python with pandas and scikit-learn, plus familiarity with a deep learning framework.
- Understanding of model evaluation concepts including overfitting, leakage, class imbalance, and metric selection.
- SQL and practical data engineering skills.
- Testing, code review, version control, continuous integration, and production debugging experience.
- Comfort with at least one cloud platform and containers.
- Fluent and responsible use of AI coding tools and agents.
- Ability to raise problems early.
Useful Experience
- Digital public infrastructure such as registries, credentials, wallets, or data exchange.
- Offline-first or low-connectivity systems.
- Production language models, retrieval, or forecasting.
- Government or large institutional systems.
- Open-source contributions.
Additional Requirements
- Successful completion of a reference check and employment verification is required.
- Candidates must not have a former-employer restriction that prevents performance of the role.
- Candidates must declare current or recent engagements with government, multilateral, or development finance institutions that could create a conflict of interest.
- Responsible and sophisticated use of AI is mandatory for all roles.
Position Details
- Position type: full time, permanent.
- Location: India, with regular travel to client sites.
- Travel is expected at 20 to 25 percent.
- The role reports to the Staff Engineer, Embedded AI.
- The level and grade are L4, manager equivalent on the Embedded AI Engineering band.
About APLYD and Athena Infonomics
APLYD helps governments, multilateral institutions, development finance institutions, and foundations use AI in public systems.
The organization covers strategy and readiness, field data, design and build, evaluation and audit, and production scale.
The group reports more than 440 engagements, 240 global clients, 85 specialists, seven countries, and five continents.
Work Culture
The work environment is outcomes-based, with flexible hours and substantial autonomy.
The company supports professional development, on-the-job training, thought leadership, and leadership pathways.
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