Sales Executive

Springer Capital is a cross-border asset management firm specializing in real estate investment banking between China and the USA. We are offering a remote internship for aspiring data engineers interested in data pipeline development, data integration, and business intelligence. The internship offers flexible start and end dates. A short quiz or technical task may be required as part of the selection process. 

Responsibilities: 

▪ Design, build, and maintain scalable data pipelines for structured and unstructured data sources 

▪ Develop ETL processes to collect, clean, and transform data from internal and external systems 

▪ Support integration of data into dashboards, analytics tools, and reporting systems 

▪ Collaborate with data analysts and software developers to improve data accessibility and performance 

▪ Document workflows and maintain data infrastructure best practices 

▪ Assist in identifying opportunities to automate repetitive data tasks 

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).

Manual and Automation testing

CICS( MAINFRAME)

TOSCA

SQL and Playwright are desirable

Years of exp – 6+ yrs

Location – Chennai & Pune

Work Mode – 5 days WFO

Notice Period – Immediate Joiners

🌟 We Are Hiring! 🌟

🚀 Launch Your Career in Digital Marketing with UpTeams App! 🚀

UpTeams App is on the lookout for passionate freshers and digital marketing course graduates to join our growing team!

🌟 Key Skills Required:

✅ Strong Communication Skills

✅ Creative Content Creation

✅ Campaign Management Expertise

📍 Location:

EliteEvince Technologies,

A-713, Dev Aurum Commercial,

Deer Circle, Prahladnagar, Ahmedabad

Selected intern's day-to-day responsibilities include:

1. Conducting market research and analysis to identify potential business opportunities

2. Creating and delivering presentations to potential clients and partners

3. Identifying and contacting potential clients and partners, and following up with leads

4. Assisting with creating sales collateral, such as brochures and presentation

5. Maintaining and updating customer and prospect databases, tracking key metrics, and reporting on performance

6. Staying current with industry trends and best practices, attending conferences and networking events, and sharing knowledge and insights with the team

7. Completing administrative tasks as needed, such as scheduling meetings, organizing files, and managing project timelines

1. Create Exclusive Distributors (minimum 4 in 4 months) in your respective areas of operation

1. To work directly with the distributor and the sales executives in designing and implementing key marketing campaigns.

1. To actively engage yourself to collect inventory, stocks and work reports of the distributor in a

daily/weekly basis.

1. To look after smooth functioning and supply chain of the authorized distributor under your

periphery.

1. To oversee sales executive schedule and plan them accordingly.

1. To facilitate cross-functional communications among project stakeholders.

1. To actively engage yourself with core marketing policies required for business development.

1. To look after the grievances and claims arising from time to time maintaining proper

coordination with the company.

1. To actively follow other marketing strategies and instructions as and when instructed by the company.

Anahad is India’s fastest growing chain of branded pharmacies and e-pharmacy, started and run by IIT Bombay Alumni.

At Anahad, our mission is to make genuine medicines reach EVERY INDIAN HOUSEHOLD at Wholesale prices, by leveraging the efficiencies of technology. Working on an audacious mission it becomes important to have people who are smarter than you around. We are funded by some of the coolest investors of Silicon Valley, India and Japan and now want YOU to join our mission.

Anahad aims to consolidate and build a household brand in a largely unorganised market worth more than 1.5 Lakh Crore. We are looking for dynamic Pharma professionals who are striving to grow fast and create an identity for themselves in the Pharma industry.

JD : Medical Representative Sales

Role:

1. Tie up with Pharmacies for execution of customer orders received through Anahad App

2. Get company agreement signed by pharmacies in specified timelines.

3. Train Pharmacies on the process for receiving , processing and execution of Anahad App orders

4. Coordinate with call centre team for resolving execution issues of partner pharmacies

5. Manage payment settlement with partner pharmacies

6. Ensure timely submission of reports by partner pharmacies like GMV, product wise sale report, etc.

Candidate Profile:

1. Must have atleast two years experience as sales executive in a reputed Pharma company, preferably Over the counter (OTC) or consumer division.

2. Must have worked in the same geography/City for atleast one year

3. Must have good rapport with the Pharmacies and top Distributors in the city

4. Must have own two wheeler for better mobility to be used for company field work.

5. Must have good working knowledge of the terms and conditions of the Pharma Distribution channel prevailing in the city like discount offered by distributors to pharmacies, payment terms, discount offered by pharmacies to customers, etc.

Location : Mumbai