L1/L2 Laptop/LAN Support Technician

About the Role

We are looking for a highly performance-driven and growth-focused marketer to lead our digital acquisition and paid marketing initiatives across Meta, Google, and D2C channels.

This is a hands-on role for someone who can independently manage performance marketing, build creative strategies for ads, scale campaigns profitably, optimize ROAS, and drive measurable business growth for a fast-growing D2C wellness and lifestyle brand.

The ideal candidate should understand D2C consumer psychology, ad creatives, content hooks, funnels, and data-driven campaign optimization.

Core Objectives of the Role

* Scale online sales profitably through performance marketing

* Improve ROAS while reducing CAC

* Build high-converting creative strategies for ads

* Increase customer acquisition and conversion rates

* Test creatives, hooks, offers, and audience segments regularly

* Improve retention and remarketing performance

* Build scalable growth systems for the brand

* Drive measurable revenue growth through paid channels

* Support overall D2C brand growth and profitability

Key Responsibilities

* Independently manage Meta Ads (Facebook & Instagram)

* Manage Google Ads campaigns (Search, Shopping, Display, YouTube)

* Plan, launch, optimize, and scale paid campaigns

* Develop creative strategies for performance ads

* Suggest ad hooks, angles, scripts, thumbnails, and concepts

* Coordinate with designers, editors, and content teams

* Analyze winning creatives and performance trends

* Monitor ROAS, CTR, CPC, CPM, CAC, CVR, and other key metrics

* Build audience targeting, retargeting, and scaling strategies

* Improve conversion funnels and customer journeys

* Conduct competitor and market research

* Work closely with founders on growth initiatives

* Generate actionable reports and performance insights

* Use tools like Canva, ChatGPT, Google Analytics, Shopify, and Ads Manager

Required Experience & Skills

* Minimum 3 years of hands-on performance marketing experience

* Strong expertise in Meta Ads Manager

* Working knowledge of Google Ads

* Experience with D2C/eCommerce brands preferred

* Strong understanding of ROAS, CAC, LTV, CTR, CVR, CPC, CPM

* Strong understanding of creative strategy and ad psychology

* Ability to identify winning ad angles and hooks

* Familiarity with Canva or creative editing tools

* Strong analytical and execution skills

* Ability to work independently in a startup environment

Compensation & Benefits

* Annual CTC: Up to ₹6,00,000

* Attractive ESOP opportunities

* Performance-based incentives and bonuses

* Direct exposure to scaling a fast-growing D2C brand

* High ownership role with founder-level collaboration

* Fast-paced startup learning environment

Ideal Candidate Traits

* Data-driven and performance-focused

* Strong ownership mindset

* Creative + analytical thinker

* Fast executor and problem solver

* Deep interest in consumer psychology and ad performance

* Comfortable working in startup environments

As an Associate Technical Architect - Data, you will lead the end-to-end design, architecture, and implementation of enterprise-scale AWS data platforms and Lakehouse solutions. You will provide technical leadership across the entire project lifecycle—from solution architecture and technology selection to implementation, optimization, deployment, and production support.

The role requires deep hands-on expertise in modern AWS data engineering technologies, strong architectural skills, and the ability to mentor engineering teams while collaborating with business and technical stakeholders to deliver scalable, secure, and high-performance data solutions.

Must Have Skills:

• 8+ years of experience designing and delivering enterprise-scale Data Lake, Lakehouse, or Data Warehouse solutions on AWS.
• Proven experience leading end-to-end implementation of cloud-native data platforms, including architecture, design, development, deployment, and production support.
• Strong hands-on expertise in SQL (analytical queries, window functions, stored procedures), Spark/PySpark, and Python.
• Strong hands-on experience designing and implementing Lakehouse architectures using Apache Iceberg.
• Strong knowledge of AWS services including EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, CloudWatch, SQS, SNS, EventBridge, IAM, and related AWS data services.
• Experience designing and implementing scalable batch and streaming data pipelines using AWS native services.
• Strong expertise in Spark/PySpark performance tuning and optimization.
• Hands-on experience optimizing Apache Iceberg and Aurora PostgreSQL for performance, scalability, and cost efficiency.
• Strong understanding of data modeling, distributed data processing, partitioning strategies, file formats, and Lakehouse/Data Lake architectures.
• Strong understanding of AWS architecture principles, including security, networking, disaster recovery, scalability, resiliency, and cost optimization.
• Experience designing orchestration workflows using Apache Airflow or AWS Step Functions.
• Ability to define cloud data platform architectures, evaluate technology choices, and articulate architectural trade-offs and best practices.
• Experience leading globally distributed engineering teams, mentoring developers, conducting architecture/code reviews, and driving engineering best practices.
• Excellent communication, stakeholder management, problem-solving, and technical leadership skills with the ability to translate business requirements into scalable technical solutions.
• AWS Solution Architect Associate/Professional or AWS Data Engineer Associate certification is preferred.

Good to Have Skills:

• Experience with ClickHouse, including performance tuning and query optimization.
• Experience with Infrastructure as Code using Terraform or CloudFormation.
• Experience implementing CI/CD pipelines for data engineering workloads.
• Exposure to Kafka, Hive, HDFS, or other Big Data technologies.
• Hands-on experience using GenAI-assisted development tools such as Kiro, GitHub Copilot, Cursor, or similar AI coding assistants to improve engineering productivity.
• Experience integrating with data governance and metadata management tools such as Collibra.
• Experience integrating with data virtualization platforms such as Denodo.
• Telecom/Mobile Network domain knowledge is preferred but not mandatory.

About the role:

Unico Connect is an Al-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Senior Al Engineer for a dedicated client engagement focused on building an Al-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code. The mandatory requirement for this role is hands-on production experience shipping LLMpowered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage. The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy. You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent architecture: Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions. Make and revisit architectural decisions on singleagent vs. multi-agent designs, including planner/executor splits and dedicated buildrepair sub-agents.

Code generation pipeline: Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit. Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies. Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-repair loop: Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation. This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context management: Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval. Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes. Own token budgeting and prompt caching strategy.

Prompt engineering as a discipline: Own the system prompt and per-task prompt variants (new feature, bug fix, styling change). Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites. Version prompts like code with changelogs and rollback capability.

Evaluation and quality measurement: Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant. Define regression gates that block qualitydegrading changes from shipping. Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time. This responsibility is nonnegotiable at this level. 

Model strategy and cost: Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation. Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection. Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and reliability of agent behaviour: Defend against prompt injection from user content and fetched web content. Ensure secrets never appear in generated client code. Define what the agent's tools may and may not do in collaboration with the platform team. Contribute to output moderation and abuse-pattern awareness.

Mentorship and engineering standards: Run code reviews, define engineering conventions for Al work, and raise the engineering bar across the Al team. Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on production ownership of LLM-powered systems with agent architectures (mandatory). Must have personally shipped and operated at least one complex production Al system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost. POCs, internal demos, and tutorialgrade work do not qualify.

5+ years of professional software or Al engineering experience, with at least 3 years focused on LLM applications, Al engineering, or production Al systems. Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python proficiency and service development. Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging. Not notebook-only. 

Depth across LLM APIs and agent systems. Production experience with at least two of OpenAl, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together). Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, Llamalndex Agents) or hand-rolled equivalent. Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, systematic evaluation practice - non-negotiable. Must have built evaluation harnesses that gate production releases, not ad-hoc testing. Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval. Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost discipline for production Al. Track record of measurable cost optimisation on production Al features. Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS working knowledge. Hands-on with EC2, S3, IAM, and Docker. Comfort with CI/CD workflows and deploying Al services.

Awareness of LLM security failure modes. Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to have: experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work; MCP server authoring; open-source Al contributions; published technical writing on LLM systems; multi-modal model experience; fine-tuning exposure (LORA, QLORA, PEFT).

1. Lead the development of frontend architecture and implement scalable, maintainable, and

high-performance web applications.

2. Conduct code reviews and provide constructive feedback to team members to ensure adherence to best

practices and coding standards.

3. Mentor and guide junior frontend developers, fostering a culture of continuous learning and

improvement.

4. Stay up-to-date with the latest frontend technologies, frameworks, and industry trends, and integrate new

solutions as appropriate.

5. Coordinate with the project management team to ensure the timely delivery of high-quality frontend

components and features.

6. Contribute to the development of reusable components, tools, and libraries to improve team productivity

and code maintainability.

Your Tasks:

• Participate in all aspect of operation and application support.
• Work primarily in Java-on-Java Spring and web frameworks like Bootstrap and Vue.js.
• Engage and collaborate across time zones with different front-end and back-end developers.
• Working closely with your teammates on knowledge sharing and experience build-up.
• Drive development best practices with your teammates to deliver high quality solutions. 

  Your profile:

• Bachelor’s degree in computer science, information technology, or engineering with strong communication skills.
• 4+ years of experience building large-scale software applications or web applications
• Strong knowledge of Full-Stack development with Java Spring Framework and established web frameworks Bootstrap, Vue.js, React or AngularJS.
• Experience of different data stores and search engine solutions like Apache Solr or Elasticsearch and designing and implementing API web services (RESTful and SOAP-based)
• Ability to work independently and collaboratively in a multidisciplinary team environment whiles providing operational support capability.