Merito is a curated talent platform where we identify, assess, and connect candidates for matching job opportunities. We are working with the mission to change the way hiring is done. The company is founded by a team consisting of alumni from IIM Ahmedabad, McKinsey will more than 2 decades of experience in recruitment, training, and coaching.
About our Client :-
Our client is a B2B2C tech firm backed by a Retail Giant and tech venture capitalist founded by founders - IITB Graduates who are experienced in retail, ecommerce and fintech.
The company aims to become one app to manage all your brands loyalty points, cashback and coupons. It will have additional content and discovery layer for customers and brands for further engagement and commerce.
Responsibilities :-
- Find insights that influence decisions (particularly new product/feature ideas). This work will span from early data explorations about user behaviour, to multivariate experiments and optimisations
- Analyse and provide recommendations to influence our product and marketing strategy
- Provide user insights through data: cohorts analyses, user segmentation, and behavioural analyses
- Challenge status quo and drive data-driven performance optimizations to improve campaign performance and user engagement on the website
- Track & analyze the consumer growth metrics - Lifetime Value, Acquisition Cost, Cohorts, customer life cycle, etc.
Required Skills :
- Advanced problem solving skills
- Expertise in deriving insights from large datasets across multiple sources
- Excellent proficiency in SQL & a knack for learning how to build data sets/tables
- Experience in Google Analytics (Good to have)
Shubham Vishwakarma
Full Stack Developer - Averlon
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Amazon Web Services (AWS)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
Adobe IllustratorWe are looking for an experienced and creative Video Editor to join our team! As a Video Editor at our company, you will be responsible for editing, and producing photos and videos from stock images and videos, for internal and external purposes.
As video has become the best way to communicate the company's messages on online platforms, your position will play an important role in our company's success.
You’ll edit them accordingly per the requirements.
Experience and complete knowledge of video editing software like Adobe Premiere Pro, light works, etc
Experience as a graphic designer or in a related field.
Demonstrable graphic design skills with a strong portfolio.
A strong eye for visual composition.
Effective time management skills and the ability to meet deadlines.
Amazon Web Services (AWS)Nvizion Solutions is looking for the position of Site Reliability Engineer.
If interested, kindly share your resume along with contact details.
Title: Site Reliability Engineer
No. of job openings: 2
Location:Gurgaon/ Hyderabad/ Bengaluru/ Mumbai/Chennai ( Remote location)
Remuneration:Best in the Industry
· Experience required: 2 to 4 yrs in the industry
· Ensuring overall System's reliability
· Add automation and alerting in the system
· Providing Troubleshooting support
· Cross team communications. Working closely with Product team and Customer success team.
· Proactive support - to ensures the system is back to the healthy state
· R&D for new tools/technologies to support product and support team
· Good verbal/written communication to connect with the client.
· Good team player with a zeal to learn new technologies.
· The candidate will be part of the team responsible for 24X7 monitoring of distributed global platform.
- Linux Scripting
- CI/CD knowledge (Jenkins/ BitBucket Pipelie /GitOps)
- Version Control
- Cloud platform knowledge (GCP/AWS/Azure/Digital Ocean)
- Docker, Kubernetes
Profile Summary:
Performance engineers should be proficient in any of the programming languages. One should not only a programmer but one who can do testing. Performance Engineer must then run those tests, analyse the results, and provide appropriate solutions to help enhance system performance, reliability, and scalability. They are also often required to work with engineers and developers to perform bug fixes.
Skills Required:
1. A performance engineer must be familiar with either one of the C, C++, C# or .Net, Java, Python (programming languages). Strong knowledge on any one of the programming languages is must.
2. Strong Software Development Skills
3. Experience with Logging and Performance Tools
Tools: Apache JMeter, MS VSTS, Shell, Jenkins, Dynatrace, Datadog, Splunk
4. Program Scripting
5. Experience in Database Profiling with one the standard database- SQL Server, MS SQL
6. Strong logical reasoning/ building
Experience: 3-4+ yrs
1. Work on lead generation via joining the Twitter community, Telegram groups, LinkedIn, and other professional and social media networks
2. Manage a pipeline, generate new leads, identify and contact decision-makers, screen potential business opportunities
3. Manage recurring prospects while engaging with new clients, educating, and optimizing for value and brand awareness
4. Generate leads and build relationships by nurturing warm prospects and finding new potential sales outlets
5. Handle inbound requests generated via the sales and marketing team
6. Identify best practices to refine the company's lead generation playbook
7. Partner with other teams to provide market intelligence that enables better decision-making in strategic areas like product development, product improvement, and market strategies among other things
8. Utilize CRM, and multiple communication channels, to generate new sales opportunities
9. Build long-term trusting relationships with prospects to qualify leads as sales opportunities
10. Seek out new business opportunities and thrive in the startup ecosystem
11. Report to the assigned manager with weekly, monthly, and quarterly results
12. Persuade, lead, and confidently handle objections and resolve customer issues
13. Showcase ownership of the clientele/leads assigned
- Analyzes, designs, develops, codes and implements programs in one or more programming languages, for Web and Rich Internet Applications.
- Supports applications with an understanding of system integration, test planning, scripting, and troubleshooting.
- Assesses the health and performance of software applications and databases.
- Establishes, participates, and maintains relationships with business units, customers and subject matter experts in order to remain apprised of direction, project status, architectural and technology trends, risks, and functional/integration issues.
- Defines specifications and develop programs, modifies existing programs, prepares test data, and prepares functional specifications.
- Analyzes program and application performance using various programming languages, tools and techniques.
- Provides guidance to non-technical staff in using software and hardware systems most effectively and efficiently.
- Reviews project proposals, evaluates alternatives, provides estimates and makes recommendations.
- Designs and defines specifications for systems.
- Identifies potential process improvement areas and suggests options and recommends approaches
- Knowledgeable in software development and design pattern
- Swagger, Rabbit MQ, Kafka
- Good API skills technology such as Rest web service and Spring based technology
- Good knowledge on Container based application configurations and deployment preferred env. is OpenShift
- Experience on creating unit test using Junit
- Experience on markup language such as JSON and YML
- Experience on using quality and security scan tools such as Sonar, Fortify
- Experience on Agile methodology
- 7 -10 Years of experience in software development.
NodeJS (Node.js)
React.js
PHP
Python
Ruby on Rails (ROR)Responsibilities:
Building Scalable Application from ground-up.
Design and Implementation of Data Storage / Schema
Building reusable code and libraries for future use.
Skills And Qualifications:
Experience with MongoDB, AWS, NodeJS, Express, React.js
User authentication and authorization between multiple systems, servers, and
environments Integration of multiple data sources and databases into one system Management of hosting environment, including database administration and scaling an application to support load changes
Data migration, transformation, and scripting Creating database schemas that represent and support business processes Proficient knowledge of a back-end programming language (NodeJS,) Proficient understanding of code versioning tools, such as Git, Understanding of “session management”.
C#Mandatory Requirement/ Preference:
- 4 years of experience for delivering enterprise solutions or products using full SDLC
- 4 years of work experience with enterprise solutions for Microsoft platform (SQL Server, stored procedures, WCF, C#.net, Entity Framework)
- Extensive knowledge and experience with creating and maintaining stored procedure in MS SQL Server.
- Working with WEB API added advantage
PHP
CodeIgniter
CakePHP
Laravel
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Full Stack Developer - Averlon