Job Description
We have immediate opportunity for Prompt Engineer5+ years – Synechron – Mumbai
Job Role: - Prompt Engineer
Job Location: - Mumbai (Goregaon)About Synechron
About Synechron
Synechron is a global technology consulting firm that helps leading organizations accelerate digital transformation through innovation, expertise, and agility. With more than 16,500 professionals across around 60 offices in over 20 countries, we combine deep industry knowledge with advanced capabilities in AI, cloud, cybersecurity, and data engineerin
g.Our regional teams, supported by strategic delivery centers, provide scalable, cost-efficient solutions tailored to local markets. Through our award-winning Synechron FinLabs accelerators and strategic partnerships with AWS, Microsoft, Databricks, Salesforce, and ServiceNow, we enable clients to innovate fast and lead with confidence. For more information on the company, please visit our website or LinkedIn communit
Responsibilities Technical Skills:
- 5+ years experience in prompt engineering, NLP, ML product development, or related roles
- Strong practical experience with large language models (e.g., OpenAI, Anthropic, Llama-family) and prompt design
- Proficiency in Python and experience with model inference frameworks (Transformers, LangChain, or similar)
- Experience with evaluation frameworks, A/B testing, and metrics for language models
- Familiarity with data labeling, annotation workflows, and prompt-based data augmentation.
- Solid understanding of ML safety, bias mitigation, and content policy considerations.
- .Excellent written and verbal communication skills
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With below details (Mandatory)
Total Experience
Experience in Prompt Engineer
Current CTC
Expected CTC
Notice period
Current Location
Ready to relocate to Goregaon,
MumbaiIf required available for F2F round :
Open for 12 PM to 9 PM shift
If you had gone through any interviews in Synechron before If Yes
Regards,
Pravin [HIDDEN TEXT]
Hp & WhatsApp # 8956217056
More Info
Key Skills
Prompt engineering
Content policy considerations
Bias mitigation
Prompt-based data augmentation
ML safety
Annotation workflows
Metrics for language models
Prompt design
Data labeling
Evaluation frameworks
