TL Sales

Senior MLOps Engineer

LLM Operations, Observability & Eval Infrastructure

📍 Mumbai (On-site) | Full-time | 5-7 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior MLOps Engineer for a dedicated client engagement focused on building an AI-powered application builder platform. The platform consumes LLMs at scale through provider APIs.

This role owns the operational discipline around production LLM consumption - increasingly called LLMOps - covering observability, evaluation infrastructure, model lifecycle, cost operations, prompt deployment, and agent run reliability.

The mandatory requirement is hands-on production experience operating LLM-backed systems, with a strong DevOps or SRE foundation. This is not a model training or ML science role.

The work is making the system around the AI engineer's designs observable, controlled, reliable, and economically accountable. You will pair daily with the Senior AI Engineer, who designs prompts, evals, and agent behaviour - you operationalise those systems for production.

A typical week includes a tracing audit on a degraded agent run, an eval pipeline build for a new model release, a cost attribution review, and a staged prompt rollout.

Responsibilities:

Observability and Tracing

Build and own end-to-end tracing for agent runs: every prompt, response, tool call, token count, latency, and cost, linked to user session and project.

Stand up and operate LLM observability tooling (Langfuse, LangSmith, Braintrust, or Arize Phoenix).

Make debugging a single bad agent run among thousands a routine workflow through searchable traces, failure taxonomies, and dashboards segmented by task type.

Evaluation Infrastructure as a Production System

Operationalise the eval suite designed by the Senior AI Engineer: automated execution in CI on every prompt or model change, with results stored and trended over time.

Implement regression gates that block quality-degrading changes from shipping.

Build production sampling to continuously score a sample of real agent runs and catch quality drift that offline evals miss.

Model Lifecycle Management

Pin model versions, never "latest".

Own the upgrade process: run the eval suite against new model releases and manage eval-gated migrations.

Maintain fallback chains across providers for graceful degradation or queueing during outages.

Track provider deprecation schedules and plan migrations ahead of forced cutoffs.

Cost Operations

Implement per-user and per-task cost attribution - token spend is the platform's largest variable cost and requires the same rigour as cloud cost management.

Set up budget alerts and anomaly detection so a single user or bug cannot burn significant spend overnight.

Monitor prompt cache hit rates and quantify savings.

Manage capacity planning around provider rate limits, including quota negotiation and throughput tiering.

Prompt and Configuration Deployment

Treat prompts as production artifacts: version control for prompts and agent configurations, staged rollout infrastructure (deploy a prompt change to a percentage of traffic before full rollout), A/B testing infrastructure, instant rollback, and audit history covering which prompt version served which user and when.

Reliability Engineering for Agent Runs

Agent runs are long, stateful, and failure-prone.

Own retry and resume semantics so a run that fails mid-way does not restart from scratch.

Implement timeouts and circuit breakers on provider calls, dead-letter handling for failed runs, and queue and concurrency management for agent workloads.

SLO Ownership and Incident Response

Define and track SLOs for agent run latency and completion rates.

Lead incident response when SLOs are breached.

Write postmortems.

Surface reliability risks proactively before they reach users.

Safety and Compliance Operations

Run the moderation pipeline (prompt and output classification) in production.

Monitor for abuse patterns and own incident response when the agent misbehaves at scale.

Maintain audit logs and implement data retention and residency policies for prompts and generated code as enterprise requirements emerge.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day for infrastructure code, scripts, and pipelines.

Set the team standard for safe use, review, and validation of AI-generated infrastructure before it ships.

Requirements:

Hands-on production ownership of LLM-backed systems in operation (mandatory).

Must have personally shipped and operated at least one LLM-powered system in production, with operational responsibility including oncall, incident response, and reliability ownership.

Alternatively: strong DevOps or SRE background with demonstrated hands-on familiarity with LLMOps tooling (Langfuse, LangSmith, Braintrust, Arize, or equivalent).

POCs and lab work do not qualify.

5+ years of overall engineering experience

With at least 2 years in DevOps, SRE, platform engineering, or LLM operations roles.

This is not an ML science role.

A DevOps or SRE background with a substantive pivot into LLMOps is a strong qualification.

Observability and Tracing Depth

Production experience with LLM observability tooling - Langfuse, LangSmith, Braintrust, or Arize Phoenix.

Comfortable instrumenting with OpenTelemetry, Prometheus, and Grafana.

Able to build and search trace pipelines, define failure taxonomies, and surface quality signals from production traffic.

CI/CD and Quality Gate Experience

Strong with GitHub Actions or GitLab CI.

Experience building automated quality gates: eval-gated pipelines, regression enforcement, or coverage gates that block degrading changes from shipping.

Cost Management and Attribution for Usage-Based Services

Experience owning cost attribution for cloud API spend or equivalent.

Comfortable with budget alerts, anomaly detection, and per-user or per-task cost breakdowns.

Reliability Engineering for Long-Running, Stateful Workloads

Experience with queues, retry patterns, idempotency, and failure recovery on asynchronous or multi-step workloads.

Comfortable defining SLOs and being accountable for them on production systems.

Multi-Provider API Management

Familiarity with LLM provider rate limits, version pinning, fallback chains, and quota management across OpenAI, Anthropic, Google, or equivalent.

Infrastructure as Code and Deployment Automation

Hands-on with Terraform or Pulumi and Docker.

AWS working knowledge (EC2, S3, IAM, EKS or ECS).

Strong with CI/CD for deploying services and configuration changes safely.

Nice to Have

• Experience with prompt A/B testing or staged rollout infrastructure
• Workflow orchestration (BullMQ, Temporal, Celery)
• Content moderation pipeline experience
• Data residency and compliance requirements for AI systems
• Kubernetes (EKS) in production
• AWS certifications

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

Required Skills & Qualifications:

✔ Experience: 4+ years in Cloud Engineering, with a focus on GCP.

✔ Cloud Expertise: Strong knowledge of GCP services (GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Functions).

✔ Kubernetes & Containers: Experience with GKE, Docker, GKE Networking, Helm.

✔ DevOps Tools: Hands-on experience with Azure DevOps for CI/CD pipeline automation.

✔ Infrastructure-as-Code (IaC): Expertise in Terraform for provisioning cloud resources.

✔ Scripting & Automation: Proficiency in Python, Bash, or PowerShell for automation.

As a senior engineer you will be working independently in designing and implementing new visuals and also helping improve code quality. A lot of emphasis is on usability; so any specific experience is ux is a big plus. Any experience with backend implementation is also a plus

You will work with a mix of front end technologies, primarily JavaScript, D3, HTML 5, SVG, CSS (and related tech like SaSS/LESS). You'd also work with Git, WebPack. You don't already need to know all of these technologies.The key requirement is a keen interest in UI/UX work, solid front-end programming skills (thorough understanding of JavaScript, CSS and browser rendering workflow) and critical thinking.

Remote working is allowed

Please find the Job Description for C/C++.

Mandatory Skills

-Must have experience and Good understanding about pointers & memory in C/C++

-Must have experience in Unix/Linux IPC (semaphore, shared memory, socket, multi thread)

-Must have Debug skills : gdb, coredump analysis, network packet analysis

-Must have experience in Source code syntax parser (Preferably lex, yacc, bison, etc.)

-Must have worked on build tools : Makefiles, make, etc.

-Database : Preferably Oracle Good at SQL and stored procedures

Optional Skills

-Telegram development using C/C++

-Finance/Industry domain knowledge

-Japanese speaking skills

• Responsibilities:Troubleshoot and report RCA, propose solutions(how to fix)
• Debug identified problems and provide fixes swiftly
• Ability to write clear and concise documentation
• To understand and maintain legacy codebase
• Individual contributor, but also works closely with junior developers
• Review source code developed by peers
• Proactive to suggest and implement improvements on current products
• Design and develop new features based on requirement document

Location-Bangalore

Please share your updated resume to proceed further.

Thanks & Regards

Shruti(Assistant Executive-HR)

Nichi-In Software Solution Pvt Ltd

URL:- www.nichi.com

• Measure impact and perform analysis to improve KPIs.

Roles and Responsibilities :

• Design, Develop, test and maintain software applications with MVC architectures, Microservices and scalable cloud-native apps.
• Perform hands-on coding and provide thoughtful code reviews
• Mentor and lead team members to continuously improve the quality and productivity of deliverables
• Demonstrate ability to work within an agile team as well as collaborate with many other teams on design and implementation strategies. Follow SCRUM Agile Development methodology
• Effective Communication Skills- An ability to express your ideas to the recipient & Co-ordinate and communicate with the cross-functional team along with the client's team
• Problem Solving, Hustler - Get Stuff Done, Self-Disciplined Open-minded, User-Focused, Adaptive
• Lean Principles & Analytical Thinking
• Project planning, timelines and milestones for execution and deliverables
• Participate in the Evaluation Review of your team member

Primary Skills

• Expert in Python with experience on Django.
• Expert in server programming, you should be able to implement complex business logic.
• Good understanding of the threading limitations of Python, and multi-process architecture.
• Good understanding of fundamental design principles behind a scalable application.
• Knowledge of event-driven programming in Python.
• Experience with python packages like Numpy, pandas, flask, Pyspark, pymongo, os, logging, re, pyyaml.
• Experience with swagger io module to expose API
• Strong unit test and debugging skills.
• At least 2 years of experience in RESTful API/HTTP/JSON`
• Knowledge of AWS cloud and python Boto lib.
• Proficient understanding of code versioning tools Like Git.
• Good understanding of Linux OS.

Secondary Skills:

• AWS Kinesis
• Web Sockets
• RAbbitMQ
• AWS Cloud formation

Senior Dotnet Developer

About the Company:

TransformHub is a An ISO 27001 certified Company adhering to a Gold standard in Information Security. It is multi-award-winning Global Digital Solutions company providing a full suite of digital transformation & product engineering services to enterprises, product companies & new-age start-ups. We have our presence in Singapore, USA, Canada, Middle East, UK and India. Our mission is to become a preferred partner to enterprises for growth and innovation in the digital age. TransformHub combines Strategy, Experience, and Technology at every stage of the engagement model to build human-centered digital platforms & channels. Our expertise lies around the 6 building blocks for Digitization - Product Engineering, Mobility, Enterprise Integrations, Data & Analytics, Cloud & DevOps, Intelligent Automation. With a large and ever-growing team of digitally ready consultants, the company helps its clients to grow and stay ahead of their competition. TransformHub has been featured into leading magazines like IndustryWired and CIOReview as Top 10 Digital Transformation Providers.

Responsibilities 

• Develop new applications or make enhancements to existing applications. 
• Analyze user requests and assist with design activities. 
• Collaborate with Client and translate business requirements into well-designed technical solutions. 
• Develop components based on business and/or application requirements. 
• Manage and assist with the completion of specific projects. This includes the development of web applications and web services. 
• Support applications and provide upgrades and maintenance as needed. 
• Assist software personnel in handling project related work and other requirements 
• Create and maintain documentation for application coding and project development. 
   

   Requirements  

• Familiarity with the .NET framework, C#, SQL Server database and design/architectural patterns 
• 5+ years of experience in .NET Technology Stack 
• Experience in designing databases with Microsoft SQL Server and building Web APIs 
• Excellent troubleshooting and communication skills 
• Experience working in an Agile environment (e.g. Scrum, Kanban) required. 
• Good knowledge of modern software design principles, concepts, and practices.