Business Development Executive

Senior AI Engineer

Code Generation, Agent Architecture & LLM Systems

📍 Mumbai (On-site) | Full-time | 5+ 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 AI Engineer for a dedicated client engagement focused on building an AI-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 LLM-powered 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 single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair 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 quality-degrading changes from shipping.

Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.

This responsibility is non-negotiable 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 AI work, and raise the engineering bar across the AI 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 AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.

POCs, internal demos, and tutorial-grade work do not qualify.

5+ Years of Professional Software or AI Engineering Experience

With at least 3 years focused on LLM applications, AI engineering, or production AI 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 OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).

Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex 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 AI

Track record of measurable cost optimisation on production AI 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 AI 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 AI contributions
• Published technical writing on LLM systems
• Multi-modal model experience
• Fine-tuning exposure (LoRA, QLoRA, PEFT)

What you need to have:

Social Media Manager:

We are looking for a Social Media Manager at BLITZPOKER who can enhance our brand and build strong online communities through our various social media platforms. The Social Media Manager will be responsible for developing and administering social media content that is designed to engage users and create an interactive relationship between consumers and the company. The successful candidate will also be required to collect and review social media data to develop more effective campaigns.

Roles and Responsibilities:

• Work closely with the marketing team to develop social media campaigns that help to achieve corporate marketing goals
• Develop monthly reports on emerging social media trends that will be submitted to the management and executive teams
• Monitor the company’s social media accounts and offer constructive interaction with users
• Create methods for finding and saving online customer reviews
• Analyze the long-term needs of the company’s social media strategy and offer quarterly reports to the management and executive teams that outline any necessary changes to the digital marketing plan

Qualification:

• Bachelor’s Degree in Marketing, communications, or related field
• 3+ years’ experience in social media management
• Exceptional multi-tasking skills
• Able to explain complex social media data in an understandable way
• Strong problem-solving skills
• Knowledge of Facebook’s advertising platform is required

About BLITZPOKER

BLITZPOKER is part of one of the largest poker networks in the world with over a million registrations and 100,000 active users.

In India, majority-owned by i3 Interactive Inc. BLIZTPOKER brings together all the fun and class in the world of online poker games in India with its exciting poker tournaments and promotions. It offers varieties of games in poker like Texas Hold’em, Omaha, Open Face Chinese Poker among others for professional and recreational players.

Responsibilities:

• Develop, implement, and maintain production timelines across multiple teams
• Translate product’s strategy into detailed requirements for prototype construction and final product development
• Analyze consumer needs, current market trends, and potential partnerships from an ROI
• Outline the product vision, product strategy, and product roadmap
• Assess current competitor offerings, seeking opportunities for differentiation
• Appraise new product ideas and strategize appropriate to-market plans
• Ensure that user story content and prioritization is aligned to the larger strategic objective
• Recommend the scope of present and future product lines by reviewing product specifications and appraising adjustments
• Provide information for management by preparing product sales forecasts and reports
• Meet regularly with key customer-facing teams to collect and analyze user feedback to shape new product ideas and user requirements.
• Help in the creation and maintenance of bona fide product documentation
• Work with development leads so that product requirements are understood and built accordingly
• Work within a software development methodology like AGILE
• Coordinate product releases with marketing, sales, and development teams
• Provide product training and technical expertise
• Work with the leadership team in planning the product roadmap.
• Be the product owner driving our strategic product and technology vision on the platform side of products 

Requirement:

• 3+ years of experience as a Technical Products Manager in a software company.
• Has deep knowledge of every stage of the product life-cycle -- introduction, growth, maturity, and decline -- and understands how it affects development adjustments.
• Critical thinker & problem solver
• Familiarity in the AGILE development framework will be preferable.
• Strong understanding of cutting-edge tools and technologies for frontend and backend development
• Data-oriented, have exceptional analytical skills
• Experience working with the development teams directly will be a plus
• Has the ability to set priorities and resolve issues and set realistic product development goals
• Should be able to communicate technical solutions to both internal and external audiences
• Understand industry flow and trends
• Has the ability to evaluate key metrics to optimize performance
• Demonstrated track record managing successful product development from feature definition to project deployment
• Work with product management analytics tools
• A people-friendly person with extraordinary organizational and leadership skills

The candidate for the role will be responsible for enabling single view for the data from multiple sources. 

• Work on creating data pipelines to graph database from data lake
• Design graph database
• Write Graph Database queries for front end team to use for visualization
• Enable machine learning algorithms on graph databases
• Guide and enable junior team members

B.Tech with 2-7 years of experience

Must Have

Hands-on exposure to Graph Databases like Neo4J, Janus etc..

1. Hands-on exposure to programming and scripting language like Python and PySpark
2. Knowledge of working on cloud platforms like GCP, AWS etc.
3. Knowledge of Graph Query languages like CQL, Gremlin etc.
4. Knowledge and experience of Machine Learning 

Good to Have

• Knowledge of working on Hadoop environment

• Knowledge of graph algorithms

• Ability to work on tight deadlines