Jobgether
Website:
jobgether.com
Company:
https://www.linkedin.com/company/jobgether
Seniority: Not Applicable
Industries: Internet Marketplace Platforms
Job details:
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Engineer- SaaS Platform based in India.
This is a hands-on AI engineering opportunity focused on maintaining and scaling the AI backbone of a SaaS platform.
You’ll work directly with LLM- and VLM-powered services that support content generation, compliance scoring, and campaign experimentation.
The role combines Python backend engineering, AI infrastructure, microservices, APIs, asynchronous workflows, and production operations.
You’ll be responsible for keeping AI pipelines reliable, performant, secure, and cost-efficient in a production environment.
A key part of the role involves improving model interactions through prompt engineering, evaluation frameworks, and continuous feedback loops.
You’ll collaborate closely with backend and frontend engineers to maintain a scalable and maintainable architecture.
This role is ideal for a mid-level engineer who enjoys solving production challenges and turning AI capabilities into dependable SaaS products.
Accountabilities
- Maintain and optimize LLM- and VLM-powered services supporting content generation, compliance scoring, campaign testing, and other AI-driven workflows.
- Develop and maintain production-grade Python services using Flask and FastAPI, ensuring high availability, reliability, and low latency.
- Manage asynchronous AI workflows and pipeline orchestration using Dramatiq or comparable background job technologies.
- Deploy, monitor, troubleshoot, and optimize Uvicorn/Gunicorn-based services in production environments.
- Integrate LLM/VLM routing and fallback solutions such as OpenRouter to balance model quality, latency, reliability, and infrastructure costs.
- Design and refine prompt engineering strategies that improve reliability, contextual relevance, consistency, and compliance of AI outputs.
- Build and maintain structured AI feedback and evaluation pipelines incorporating human-in-the-loop scoring, automated quality checks, and continuous improvement mechanisms.
- Design, secure, version, document, and maintain REST APIs supporting AI services and integrations.
- Collaborate with backend and frontend engineering teams to ensure microservices remain scalable, maintainable, and aligned with broader platform architecture.
- Monitor production metrics including token consumption, latency, error rates, uptime, and service health, proactively identifying and resolving performance issues.
- Support Dockerized deployments, CI/CD workflows, logging, monitoring, error handling, and production reliability practices across AI services.
Requirements
- 3–5 years of professional experience as an AI Engineer, Python Backend Engineer, or in a closely related role working with production systems.
- Strong Python programming skills and experience contributing to production-grade codebases.
- Hands-on experience with Flask and familiarity with FastAPI is highly valuable.
- Experience deploying and operating applications with Uvicorn and/or Gunicorn.
- Experience with asynchronous job queues such as Dramatiq, Celery, RQ, or equivalent technologies.
- Practical experience working with LLMs and VLMs, including prompt engineering, model evaluation, and ideally fine-tuning.
- Familiarity with LLM/VLM routing, fallback, and orchestration platforms such as OpenRouter or equivalent solutions.
- Strong understanding of microservice architecture and experience designing, maintaining, or scaling distributed services.
- Solid REST API development skills, including authentication, rate limiting, versioning, documentation, and secure endpoint design.
- Experience with Dockerized deployments, CI/CD pipelines, application logging, monitoring, debugging, and production error handling.
- Demonstrated ability to build structured AI evaluation and feedback systems that continuously measure and improve model performance.
- Experience with AWS or GCP for deploying, monitoring, and scaling production workloads is preferred.
- Experience working with SaaS platforms, AI-first products, or production LLM/VLM integrations is highly valued.
- Demonstrated ability to maintain and improve AI pipelines in production rather than working primarily with prototypes or experimental systems.
- Strong problem-solving, communication, collaboration, and ownership skills, with the ability to work effectively in a fast-moving technical environment.
Benefits
- Fully remote position based in India.
- Full-time employment within a SaaS and AI-focused product environment.
- Opportunity to work hands-on with production LLM and VLM systems.
- Exposure to modern AI infrastructure, model routing, microservices, APIs, asynchronous processing, and cloud technologies.
- Opportunity to contribute directly to AI reliability, performance, evaluation, and continuous improvement.
- Collaborative work with backend and frontend engineering teams on scalable platform architecture.
- Opportunity to develop deeper expertise in production AI engineering and SaaS platform development.
How Jobgether Works
We use an
AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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.
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